
HOCIntelligentTechnology US/UK/Canada/Germany/china/Japan
High-tech ICT×SDGs company cutting-edge science
and technology research and development
Digital
Making the most of data, algorithms, automation
and networks, we create new value
In-house R & D specialty area products
Robots, medical health IOT products, manufacturing
AI engines, autonomous driving, ERP x DX, AI cameras,etc
Keywords
Coronavirus Digitization / DX AI IoT Blockchain Security
UI / UX Big Data Data Democratization Technology
Foresight Financial Medical / Healthcare Manufacturing
HOCIntelligentTechnology China

Cutting-edge technology
AI, IOT, 5G, Blockchain, Quantum computing, ERP, EC, DX, XR, RPA, 5G, etc.
Artificial intelligence, semiconductors, 5G, quantum information science, biotechnology and green energy
Bio Technologies
- Healthcare
- Medical Technologies
- User Interface
- Design methodologies
- Welfare Technologies
- Enabling Devices and Technologies
Academic honor
A.M.TURING Award, IEEE Award, Nobel Prize, etc.










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As a network-type science and technology R & D corporation that conducts world-class research and development, we will lead ICT companies in future co-creation innovation that promotes SDGs. We will open up a prosperous future by developing and providing cutting-edge science and technology products with high quality and unique technology by creating and supporting bases in the United Kingdom, Canada, US, Germany, Japan, and China together. For our company, whose products are attracting worldwide attention, we are helping to develop products with cutting-edge technology. Utilizing the technology and know-how that has been built up at Cambridge University, MIT University oxford University, Harvard University, Dresden University of Technology, Tokyo University, Osaka University, etc., we have been working on high quality and original technology development. In order to provide safe and convenient products, we have obtained many patents related to DX BioNTech cutting-edge technology and development such as AIoT 5G blockchain quantum computing XR, AR, VR, etc., and will continue to be an "ICT company" ICT area (main area: Fintech, Communication [AR / VR], Security, Media Content, Bigdata, Cloud, IoT / Drone, Marketing / Advertising, Medical Healthcare, Robotics, Power / Battery, AI, Enterprise, Education New Energy Industry (Battery Related) Battery (Battery Related) , Hydrogen, fuel cells, etc.) and battery materials / components, etc.) We will continue to develop and evolve as SDGs business creation and development. Research and development corporation by research field (environment / energy, life science, system / information science and technology, nanotechnology / materials), hardware / software development using cutting-edge technology, demonstration experiments, research / development / operation of prototype products. Sales, cutting-edge technology R & D research field (cluster) "Future society / future technology (social implementation of Society 5.0)" "Next-generation food and planting" "Environment / energy / regeneration" "Health / longevity / development" " Creation of knowledge "e-sports construction DX sports DX, etc.





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Climate change measures decarbonization



Research and Development (R & D) arms of the Department of Science and Technology that focuses on ICT and Microelectronics
Institute for advanced science and technology
Laboratory for Systems Biology and Medicine, Research Center for Advanced Science and Technology
Advanced Institute of Science and Technology
Laboratory of Advanced Science and Technology
most-advanced science and technology
cutting-edge technology "advanced technology","cutting-edge science and technology" advanced research "advanced research"pioneer . frontier " unexplored area" hi-tech "advanced technology", "high technology" hi-tech research "advanced technology research"






ScienceandTechnologyCompny
List of our partners
Scientific Research Japan Atomic Energy Agency (JSPS), Science and Technology Agency (JST) Industry Japan Atomic Energy Agency (JAEA), Aerospace Research and Development Organization (JAXA), Ocean Research and Development Organization, and former National Institute for Testing and Materials・ Materials Research Organization (NIMS), National Institute of Radiological Sciences (currently part of National Institutes for Quantum and Radiological Science and Technology), Disaster Prevention Science and Technology Research Institute
National University Corporation: Tohoku University, University of Tokyo, Kyoto University,
Tokyo Institute of Technology, Nagoya University, Osaka University, Hitotsubashi University, etc.
New Energy and Industrial Technology Development Organization (NEDO) Japan Agency for Medical Research and Development (AMED Material and Materials Research Organization, RIKEN, etc., NTT, NTTDATA, TOYODA, etc.
We will open up a prosperous future by developing and providing cutting-edge science and technology products with high quality and unique technology by creating and supporting bases in the United Kingdom, Canada, the US, Germany, Japan, and China. We support research and demonstration experiments that utilize cutting-edge technologies such as AI (application of face recognition and deep learning), plan services and products in new technology areas, and demonstrate concept models. Industry-academia-government collaboration "Research and research in the field of advanced technology that connects advanced technology and business System consulting solution service Product solution We support companies that do their best to overcome the corona disaster!
URL: https://www.nekkyo.org/
https://www.oxhabridge.com/
https://www.nekkyoai.com/
https://www.hocintelligenttechnology.com/
HOC Intelligent Technology Co., Ltd. Osaka Headquarters Management Headquarters
4-9-35 Shuntoku-cho, Higashi-Osaka-shi, Osaka 577-0831
TEL 090-8747-9395 06-67538862
5 minutes walk from Kintetsu Fuse Station in Osaka City
R & D Center
3-15-18 Yokonuma-cho, Higashi-Osaka-shi, Osaka 577-0808
TEL 06-6720-8749 FAX 06-6720-8749
(Monday-Friday 10: 00-18: 00 * Excluding holidays and year-end and New Year holidays)
yuhong268@gmail.com info@nekkyoai.com
Osaka branch office
3-1 Ofuka-cho, Kita-ku, Osaka 530-0011
Grand Front Osaka Knowledge Capital Tower C 7th floor
Close to Nagoya branch office Nagoya station
Tokyo Branch HOC Intelligent Technology Co., Ltd. Tokyo Branch 03-6404-8082. 2 minutes walk from Omorikaigan Station on the Keikyu Line, 3-20-5 Minami-Oi, Shinagawa-ku, Tokyo 140-0013 8 minutes walk from the north exit of JR Omori Station
group company
State-of-the-art Technology Research Institute Co., Ltd.
4-9-35 Shuntoku-cho, Higashi-Osaka-shi, Osaka 577-0831
TEL 090-8747-9395 06-67208749
China local subsidiary Niuqiao Intelligence Technology Co., Ltd. High-tech company Nanjing, Shanghai, Hangzhou, Shenzhen, China, and other R & D centers and factories in Shenzhen, Taiwan, Hong Kong)
邮 KEN 210094 No. 17 Star Fire Road, Gangbuk New District, Nanjing City, China 801 Room-845
Room 801, Chuangzhi Building, No. 17 Xinghuo Road, Jiangbei New District, Nanjing, China
China Tel. 86 15358411774 1500467340@qq.com
UK subsidiary HOC Intelligent Technology
5 New Street Square, London EC4A 3TW, UK
US subsidiary HOC Intelligent Technology
Mountain View Amphitheater Parkway 160, California, USA)
Canadian subsidiary HOC Intelligent Technology
German subsidiary HOC Intelligent Technology
Living / Health Health / Medical / Welfare Culture / Art / Internationalization / Sports / Recreation / Collaboration / Community



Advanced science and technologyDNA
By field (environment / energy, life science, system / information science and technology, nanotechnology / materials)
Realization of "ultra-smart society" (Society 5.0), "11 systems" that are said to be advanced toward its realization include "promotion of community-based comprehensive care system", "smart food chain system", "smart" "Production system" is included. In addition, among the issues that should be strategically resolved, there are several related matters such as stable food security, formation of a healthy and long-lived society by realizing the world's most advanced medical technology, and improvement of competitiveness in manufacturing and manufacturing. It has been. Regarding the above-mentioned research and development related to "formation of a healthy and long-lived society by realizing the world's most advanced medical technology", based on the health and medical strategy and the medical field research and development promotion plan under the Health and Medical Strategy Promotion Headquarters. ,
The following nine main initiatives will be promoted as pillars. In addition, in other fields such as infectious disease control
We will promote international contributions, build a medical ICT infrastructure, and improve the environment for utilization.
All-Japan drug creation
All-Japan medical device development
Innovative medical technology creation base project
Realization of regenerative medicine Highway concept
Genome medical realization project for overcoming diseases
Japan Cancer Research Project
Brain and Mental Health Powerhouse Realization Project
Emerging and re-emerging infectious disease control project
R & D bird's-eye view report
R & D strategies of major countries (2020)
CRDS-FY2019-FR-02 National Research and Development, Japan Science and Technology Agency Research and Development Strategy Center
Intractable disease overcoming project
System / Information Science and Technology Field The information science and technology field has been positioned as a common basic technology that supports green innovation, life innovation, and strengthening of industrial competitiveness. In addition, as science and technology that can be used across multiple fields and science and technology in the fusion field, nanotechnology, optical / quantum science and technology, advanced information and communication technology such as simulation and e-science, mathematical science, and system science. Promotion of technology research and development is mentioned, and as a concrete initiative, basic technology required for ultra-smart social service platform
As strong as cyber security, IoT system construction, big data analysis, AI, devices, etc.
Strong robots, sensors, light, quantum, etc. as basic technologies that will be the core of technology and new value creation
It is going to be changed. The four pillars are (1) social implementation of Society 5.0, (2) strengthening of research capabilities centered on basic research, (3) drastic strengthening of international cooperation, and (4) construction of priority strategies in cutting-edge and important fields such as AI technology and quantum technology. Was included. Nanotechnology / Materials field “Nanotechnology / Materials” is one of the four priority promotion fields, and resource allocation has been focused on for 10 years along with life sciences, information and communications, and the environment. The main achievements were as follows. "Discovery of new superconducting materials including iron", "Progress in development of various materials leading to practical use including carbon fiber composite materials", "Progress in research on molecular imaging", "National core technology" X-ray
Development of R & D infrastructure such as "free electron laser" and "nanotechnology network", "Oh
Industry-academia-government collaboration by Pun Innovation Center "Tsukuba Innovation Arena" (TIA-nano)
"Strengthening", "Ministry collaboration project:" Element strategy project "(Ministry of Education, Culture, Sports, Science and Technology) and" Rare metal alternative materials
"Project" (Ministry of Economy, Trade and Industry) steady progress ", etc. In the 4th term (2011-2015), 11 systems that contribute to the realization of "super smart society" (Society 5.0) of the Institute of Physical and Chemical Research were identified from the priority area type of science and technology, and "Society 5.0" was identified as one of them. Integrated Material Development System ”Overview Report of Research and Development
R & D strategies of major countries (2020)
CRDS-FY2019-FR-02 National Research and Development, Japan Science and Technology Agency Research and Development Strategy Center
There are 28. To promote the creation of innovative functional materials, structural materials, etc. that make full use of computational science and data science.
In addition, with the goal of significantly shortening the development period, we are aware of the problem that nanotechnology and materials science and technology must continue to play a major role in the realization of Society 5.0 and SDGs. In August 2018, the Nanotechnology and Materials Science and Technology Committee of the Research Planning and Evaluation Subcommittee of the Science and Technology Council of the Ministry of Education, Culture, Sports, Science and Technology announced the "Social Revolution by Materials" that contributes to both industrial promotion and "happiness" of humankind. The "Nanotechnology / Materials Science and Technology Research and Development Strategy" was announced with the goal of realizing "(Materials Revolution)".
(3) Research infrastructure policy in the field of nanotechnology and materials
Tip. We provide cutting-edge research equipment and technical support to industry-academia-government users in three technical areas (microstructure analysis, microfabrication, and molecular / substance synthesis). It is operated by 38 institutions nationwide, including 11 institutions for microstructure analysis, 16 institutions for microfabrication, 10 institutions for molecular / substance synthesis, and a center agency responsible for overall coordination of the entire business. In addition, in collaboration with JST's ALCA next-generation storage battery project, the National Institute of Advanced Industrial Science and Technology will be in Tsukuba, where cutting-edge nanotechnology research facilities and human resources, which consist of three institutions, will be concentrated.
The National Institute for Materials Science, University of Tsukuba, High Energy Accelerator Research Organization, and the University of Tokyo play a central role in Japan.
In collaboration with the Japan Business Federation (Keidanren), a global R & D and open innovation base TIA
It is forming (from 2009). At TIA, 1. Creating Global Value, 2. Under One Roof, 3. Independence
A virtuous cycle, 4. Win-Win cooperation network, 5. Next-generation human resources development, with five principles, cooperation network with companies and universities
As a fusion base open to industry, academia and government, we will promote the industrialization of nanotechnology and human resource development in an integrated manner by promoting AI, quantum information science (QIS), and computing-based QIS, and develop and strengthen human resources. Plan and pull the industry
Prioritize research and development that provides the infrastructure that supports QIS. Sustainable and interoperable software, data maintenance and curation, and adequate security to support the research and development needed for future high-performance computing paradigms, manufacturing, devices, and architecture. Biomedical Opioid Crisis Fighting, Rapid Detection and Containment of Infectious Diseases, Drug Resistance, Prevention and Treatment of Chronic Diseases, Genetic Therapy, Neuroscience, Medical Measures and Public Health Preparation, HIV / AIDS Eradication, and More Prioritize R & D investment aimed at improving the independence, safety and health of the elderly and people with disabilities in the United States. Rapidly establish safety and efficacy for products developed using bioeconomy gene editing, adopting biotechnology products and social responsibility
Prioritize evidence-based criteria and research to promote certain uses ① "All of Us" research program (cohort study for personalized medicine)
② BRAIN (Brain Research through Advancing Innovative Neurotechnologies) Initiative
③ Cancer Moonshot
(4) Regenerative Medicine Innovation Project PCA in 2021 is also planned to be in these 11 areas.
① Artificial intelligence (AI)
② Computing for human interaction, communication, and ability improvement
(CHuman)
③ Computing (CNPS) to network physical systems
④ Cyber Security and Privacy (CSP) Education and Human Resources (EdW)
⑥ Research and development of high-capability computing system (EHCS)
⑦ High Capability Computing Infrastructure and Applications (HCIA)
⑧ Intelligent Robotics and Autonomous System (IRAS)
⑨ Large-scale data management and analysis (LSDMA)
⑩ Large-scale network (LSN)
⑪ Software productivity / sustainability / quality (SPSQ)
Innovative Medicines Initiative (IMI) 2 Innovative Medicines 30
Electronic Components & System Initiative (ECSEL) Electronic Components & Systems 50
Clean Sky (CS) 2 Air and Air Transport 40
Fuel Cells and Hydrogen (FCH) 2 Hydrogen / Fuel Cell 13.3
Shift2Rail European single rail network 9.2
Bio-based Industries (BBI) Bio-based materials and biorefining 37
Single European Sky ATM Research (SESAR) Air Traffic Management Systems, Engineering and Physical Sciences Research Council (EPSRC), Economic and Social Research Council (ESRC), and Arts and Humanities Research Council (AHRC) provide research funding Is doing only. Medical Research Council (MRC), Biotechnology and Biological Science Research Council (BBSRC), Nature
The Environmental Studies Council (NERC) not only provides research funding, but also has a research organization under its umbrella to carry out research on its own.
Giving. The Science and Technology Facility Council (STFC) manages and operates research facilities in addition to providing research funding.
ing. UKRI's 2019 budget for the study council is approximately £ 3.81 billion, using artificial intelligence (AI), data and innovation to prevent disease, diagnose early, and treat chronic illness until 2030. By 2035, at least five years longer than it is now, closing the gap between the rich and the poor
Clean growth that enables people to lead healthy and independent lives By 2030, at least halve the energy use of new buildings by 2030 Establish at least one low-carbon industrial cluster by 2040 Establish the world's first industrial cluster with zero net greenhouse gas emissions
Future Transport Means Putting the UK at the forefront of zero-emission vehicle (ZEV) design and manufacturing, 2040
Ideas for virtually zero emissions of all new cars and trucks by the year
・ Increase overall R & D investment to 2.4% of GDP by 2027
・ Increased R & D tax credit ratio to 12%
· Invested £ 725m in the Industrial Strategy Challenge Fund (ISCF)
Human resources (People)
· Invested £ 406m to promote education in STEM capabilities
・ Established a national retraining system for digital fields, etc., building technology and digital
£ 64m investment in technical training
Infrastructure
-Increased the National Fund for Productivity Investment (NPIF) to £ 31 billion, transportation, housing construction,
Promote investment in fields such as digital
· Electric vehicle (EV) support (£ 400 million in charging infrastructure investment and £ 100 million
Includes plug-in car grants)
-Invested over £ 1 billion to develop digital infrastructure (100 million for 5G)
(Including £ 76m, etc.)
Business environment
・ Start and exhibition of sector agreement (government-industry alliance for the purpose of improving productivity)
Open (as of December 2019, Space, Artificial Intelligence, Automotive, Construction, Creative Industries, Rye
Agreements with 10 sectors of science, nuclear, offshore wind, rail and tourism)
· Invest over £ 20bn in innovative, high-potential businesses
・ Small and medium-sized companies, such as how to deal with the so-called "long tail" of low-productivity companies
Conducting reviews to improve corporate productivity, etc.
Formulation of regional / regional industrial strategy
・ Launched “Urban Reform Fund” for intercity transportation and invested £ 1.7 billion
・ Launched “Teacher Development Program” and invested £ 42 million in environment and energy
UK Energy Research Center (UKERC) London (Research bases are located throughout the country)
Founded in 2004. Sustainable future energy system Conducted world-class research on It is a hub for energy research in the UK and a contact point for connecting energy research communities in the UK and abroad. It is subsidized by one of the cross-research council programs, the Energy Program for the Low Carbon Future. Life Sciences European Molecular Biology Laboratory (EMBL-EBI) Hinxton (Cambridgeshire) Established in 1992 as a division of the European Molecular Biology Laboratory (EMBL). We provide databases and conduct research related to bioinformatics. Most of the operating funds are contributed by the governments of EMBL member countries, mainly EU countries. Information Science and Technology Cambridge University Computer Laboratory Cambridge Founded in 1937. An organization at the University of Cambridge that conducts a wide range of research in areas such as computer science, engineering, technology, and mathematics. Nanotechnology and Materials Cavendish Laboratory, University of Cambridge Cambridge Founded in 1874. Institute of Physics, University of Cambridge. So far, 29 Nobel laureates have been produced. Francis Crick
James Watson discovered the double helix structure of DNA when he was at the institute, and in 1962 he won the Medical Physiology Award to improve the effectiveness of cancer treatment and strengthen cancer research to extend the lifespan of cancer patients. To do. prevention,
Improve early detection, diagnosis and treatment. Promote the digitization of patient charts and the associated strengthening of data protection. Introduce an electronic medical record system to university hospitals in Germany by 2025. Promote plant-derived plastic production by 2025 to reduce plastic waste
Or develop substances that can be efficiently recycled, and have similar challenges.
Promote research and development by collaborating with other regions.
Aim for CO2 emissions of about 85-90% in 1990 to realize the environmental protection plan 2050
It points to the improvement of production processes and the realization of a sound-cycle economy.
Creating innovative business models through efficient resource use and digitalization
Increase productivity with.
Conduct environmental assessments using innovative tools and new indicators to protect diverse species.
This area is the beginning of major innovations such as autonomous driving, electric vehicles and fuel cell vehicles.
It has been placed. Comprehensive including charging facility development, deregulation, EU policy, etc.
Implement practical measures.
Support technology development and supply chain construction for battery production in Germany.
Use the power of digital to bridge the gap between cities and regions due to changes in economic structure and demographics, and create an environment
Improve quality of life in a thoughtful manner.
With concerns about labor shortages due to the aging of the population, assistant systems and
Use robots to reduce the burden of labor. Robo in society, including safety and health
Implement comprehensive measures such as acceptance of
② Mission in future technology
With Germany and Europe as bases for AI research and development and practical application, while securing human resources
Build an AI-based business model by involving various application areas.
③ Mission in creating an open innovation environment and entrepreneurial culture
Open access, open science, open data, open inno
Contribute to the creation of the latest science through the principle of vation. Priority technology areas
Goal Priority technology
Research with an eye on social implementation and application
Machine learning, big data
Cyber security, HMI, robots, VR
Communication system, 5G communication technology
Batteries, 3D printing, weight reduction, manufacturing technology
Technology that should leap to the top of the world
Quantum simulation system, ultra-precision measurement technology, imaging
Technology
Biotechnology, bioinformatics
Aerospace satellites, materials ARENA2036 Stuttgart Great transformable automotive research
DPP RWTH Aachen University Digital Optics
Mobility2Grid Berlin Institute of Technology Smart Grid
FEN RWTH Aachen University Environmentally friendly energy
185 Cluster-Netzwerke-International
186 German name: Forschungscampus
R & D bird's-eye view report
R & D strategies of major countries (2020)
CRDS-FY2019-FR-02 National Research and Development, Japan Science and Technology Agency Research and Development Strategy Center
124
MODAL Humboldt Large Data Driven Transport / Medical Technology
M²OLIE Heidelberg Cancer Treatment
Open Hybrid LabFactory Braunschweig Institute of Technology Lightening research on vehicle materials
STIMULATE Magdeburg minimally invasive treatment
InfectoGnostics University of Jena Second Generation Quantum Computing (Computer, Simulation) as a priority area for early diagnosis of infectious diseases
Ration, etc.), Quantum communication (communication, security technology, etc.), measurement (precision measurement technology, etc.)
In addition to the development of technology, satellites, navigation technology, etc.), technology transfer in the quantum field and promotion of industrial participation
I'm sick. Autonomous driving, electric and fuel cell vehicles to solve social issues under "High-Tech Strategy 2025"
However, this area is at the beginning of major innovation. Maintenance of charging facilities, deregulation of laws and regulations,
In Germany, as a comprehensive practical measure including EU policy and a mission in the field of future technology
In addition, we will make Europe a base for R & D and practical application of AI, and involve various application areas while securing human resources.
Health, environment, and society that are shown to build an AI-based business model by doing so
Health / Digital
Digital humanity
Social / digital security
Digital, energy, environment, society
The 2020 plan also includes the following national priorities:
Artificial intelligence
Humanities and Social Sciences
Quantum technology
Drug resistance
Autism in neurodevelopmental disorders
Parallel research on rare diseases, La
Excellent based on technologies such as if science, environment / energy, ICT, and nanotechnology
The feature is that the above items are organized.
Humanities / Society, Earth System / Environmental Science, Energy, Biology / Medical Science, Materials Science / Engineering, Astronomy / Astronomical Physics, Nuclear / High Energy Physics, ICT / Mathematics, Science / Technical Information While identifying 99 concrete infrastructures, it shows the direction of support. The identified infrastructure covers the fields of global systems / environmental science and biology / medical care.
There are relatively many, with 25 and 24 infrastructures specified, respectively. Humanities / Society, Earth System / Environmental Science, Energy, Biology / Medical Science, Materials Science / Engineering, Astronomy / Astronomical Physics, Nuclear / High Energy Physics, ICT / Mathematics, Science / Technical Information While identifying 99 concrete infrastructures, it shows the direction of support. The identified infrastructures are relatively large in the fields of global systems / environmental science and biology / medical, with 25 and 24 infrastructures designated, respectively. A National Natural Science Fund Committee (NSFC272), the China Science and Technology Development Strategy Research Institute (CASTED273), which is a think tank for science and technology policy, and the China Science and Technology Information Institute (ISTIC274), which is responsible for building science and technology information infrastructure, are located. ing. In addition, the Chinese Academy of Sciences is under the direct control of the State Council, with 104 research institutes and two National Natural Science Foundations of China (NSFC).
Various programs including subsidies for basic research and applied research, human resource development, and base formation (under the jurisdiction and management of the National Natural Science Fund Committee under the Ministry of Science and Technology) National Science and Technology Problem-solving program for improving national competitiveness (under the jurisdiction of the State Council) National Key R & D Program National Key R & D Program of China
A program that consolidates problem-solving research funding from each ministry and agency
(Specialized research fund under the initiative of the Ministry of Science and Technology
Management and operation by the science agency 283)
④ Technology innovation guidance plan
Technology Transfer Program
⑤ Research base and human resources program
Base Kazuto Talented Research Center Grants and Human Resources Grants Program
Creation of new superiority through industrial technology system for promotion and development of ram innovation
(1) Next-generation information network technology, (2) Smart green manufacturing technology, (3)
Modern agricultural technology, ④ Modern energy technology, ⑤ Resource efficient use and environment
Protection technology, ⑥ Marine and space technology, ⑦ Smart city digital social technology
Art, ⑧ Health technology, ⑨ Modern service industry technology, ⑩ Industrial transformation technology Science and technology critical project
Implementation (a project that the government provides stable support over the long term)
(1) Research and development of large aircraft engines and gas turbines (2) Deep sea stays
Research ③ Quantum communication and quantum computer research ④ Brain science and brain
Research (Brain Science and Brain-Inspired Intelligence Technology)
⑤ National cyber security research ⑥ Space exploration and orbital maintenance system
Research ⑦ Voluntary breeding technology ⑧ Coal clean and highly efficient utilization technology
⑨ Smart grid technology ⑩ Top-and-bottom integrated communication network technology (satellite communication and terrestrial broadcasting)
Communication integration) ⑪ Big data technology ⑫ Intelligent manufacturing and robot
Technology ⑬ Research and development and application of new materials ⑭ Hebei Regional Comprehensive Environmental Conservation
⑮ Health and welfare technology
International competitiveness of industrial technology
Improvement
(1) Advanced agricultural technology (2) Next-generation information and communication technology (3) Advanced manufacturing technology (4) New materials
Fee technology ⑤ Green and highly efficient energy technology ⑥ Advanced transportation technology ⑦
Advanced biotechnology ⑧ Advanced food manufacturing technology ⑨ For evolution of business model
Service technology that contributes ⑩ Disruptive technology that contributes to the Industrial Revolution
Improving and maintaining the standard of living
Technology system that can be continuously developed
Build
(1) Environmental and ecological conservation technology (2) Highly efficient use of resources (3) For national welfare
Contribution technology ④ Technology related to urbanization ⑤ Technology related to public safety
Techniques related to national security and national interests
Construction of surgical system
(1) Marine resource utilization technology (2) Space exploration / space development technology
③ Ultra-deep stratum development technology
Strengthening basic research ・ Strategic basic research for social needs
① Genetic improvement of living things in agriculture ② Green use of energy
Physics / Chemistry Theory for High Efficiency ③ Information for Man-Machine Fusion
Information and communication technology ④ Integrated monitoring research of the earth system ⑤ New materials
⑥ Extreme environment (large current, strong magnetic field, ultra-high)
Manufacture in (warm / ultra-low temperature) ⑦ Disasters caused by mega-projects and their
R & D bird's-eye view report
R & D strategies of major countries (2020)
CRDS-FY2019-FR-02 National Research and Development, Japan Science and Technology Agency Research and Development Strategy Center
180
⑧ Mechanical problems related to aircraft, rockets, and spacecraft ⑨ Medical immunity
Gaku
・ Advanced basic research
(1) Nanoscience technology (2) Quantum control and quantum information (3) Tan
Control of protein complex and life process ④ Stem cell research and clinical transition
Stagflation ⑤ Advanced research by a large research facility ⑥ Global spirit
Weather fluctuations and countermeasures ⑦ Interaction between heredity and environment in development ⑧ Synthetic organisms
Studies ⑨ Genome editing ⑩ Research on deep sea, ultra-deep strata, and space ⑪ Material depth
Layered structure and astrophysics research ⑫ Mathematics and applied mathematics ⑬ Magnetic confinement Nuclear fusion As priority fields, next-generation information and communication technology, advanced digital control machine tools and robots, aviation / U
Air equipment, marine construction machinery / high-tech vessels, advanced track transportation equipment, energy-saving / new energy vehicles,
The Chinese Academy of Sciences, Tsinghua University and Beijing University have set up the National Nanoscience Center of China, which lists electric power equipment, agricultural machinery equipment, new materials, biopharmaceuticals and high-performance medical equipment.
Our center is located on the premises of the Institute of Chemistry, Chinese Academy of Sciences, and is used for nanodevices, nanomaterials, and raw materials for nanomaterials.
Body effects and safety assessment, nano characterization, nano standardization, nano manufacturing
Labs such as Hold. Industrial informatization that controls the software industry, etc.
Department, Ministry of Science and Technology, Chinese Academy of Sciences, etc.
Policy trends include the medium- to long-term plan, strategic outline, and "scientific technology" mentioned at the beginning of this section in technological development.
An important policy is set out in "The 13th Five-Year Plan for Art Innovation". In this plan, the national critical science
"Quantum communication and quantum computer" and "National cyber seki" listed in the item of technology project
"Urity", "Tenchi integrated communication network", "Next-generation information communication" listed in the item of international competitiveness of industrial technology
"Technology", "Disruptive technology that contributes to the industrial revolution such as big data and AI", "Quantum control and quantum information" technology
is there.
From the perspective of industrial promotion, "Made in China 2025" and "Internet" announced by the State Council in July 2015.
Baidu (Baidu, Baidu, the company that provides the largest search engine in China) such as "T +" and "13th Five-Year Strategic Emerging Industry Development Plan" announced in November 2016
Build a national next-generation artificial intelligence open innovation platform
(2) Alibaba Cloud, a company under the Alibaba Group, the largest cloud service in China
By "Urban Brain" (Smart City Computational Center)
Build a national next-generation artificial intelligence open innovation platform
③ "Medical image recognition" by Tencent Co., Ltd. National next-generation artificial intelligence open innovation
Build a platform
④ Kadai Hibi Co., Ltd. (IFlytek, an artificial intelligence company in the field of speech recognition and speech synthesis established in 1999)
By "Smart Voice" National Next Generation Artificial Intelligence Open Innovation Platform
To build
⑤ "AI image processing technology" by the commercial hot spring group (SenseTime) National next-generation artificial intelligence open inno
Quantum communication / quantum computing technology to build a vation platform Nanotechnology / materials field Aerospace, orbital transportation, electronic equipment, new energy
Supplying new materials that meet the needs of industries such as motor vehicles, "C
Endo general-purpose semiconductor chips and basic software, "Very Large Scale Integration (VLSI) and software"
"Russet technology", "High-end computer, numerically controlled machine tool (CNC) and basic manufacturing technology"
Work
And autonomy
Operational standards, integrated methods, traffic management systems, defense / security luck
Deployment of autonomous driving means on the ground, in the air, and at sea, with an emphasis on development for
Prioritize R & D to lower barriers to
Advanced Manufacturing Smart Digital Manufacturing Technology, Advanced Industrial Robotics, Especially
Realized by the Internet of Things (IOT), machine learning, and AI
Research Institute, Japan Atomic Energy Agency (JAEA), Japan Aerospace Exploration Agency (JAXA), Japan Agency for Marine-Earth Science and Technology,
In addition, the former National Institute for Materials Science (NIMS) and the National Institute of Radiological Sciences (currently Department of Quantum)
The National Research Institute for Earth Science and Disaster Prevention was positioned as a part of the Academic Technology Research and Development Organization). In addition, Grants-in-Aid for Scientific Research
Japan Society for the Promotion of Science (JSPS), an independent administrative agency responsible for the distribution of money and international exchange in the academic field, and science and technology
Fundy such as Japan Science and Technology Agency (JST) 3 that implements various projects that contribute to the creation of novation
There is an institution. Regarding national university corporations, part of the National University Corporation Law has been amended 4.
The world's highest level of education and research activities in order to significantly improve the level of education and research and create innovation.
The Minister of Education, Culture, Sports, Science and Technology points to a national university that operates a university based on high-level goal setting so that the movement will be developed.
The "designated national university system" to be established was launched in 2017, and is currently available at Tohoku University, the University of Tokyo, Kyoto University, etc.
Seven schools, Tokyo Institute of Technology, Nagoya University, Osaka University, and Hitotsubashi University, have been designated. In addition, science and technology
Ministry of Education, Culture, Sports, Science and Technology as a national research institute that conducts research on policy and science and technology innovation
The National Institute of Science and Technology Policy (NISTEP) is located inside. Funding and industrial technology development projects
New Energy and Industrial Technology Development Organization (NEDO), the National Institute of Advanced Industrial Science and Technology under the former National Institute of Advanced Industrial Science and Technology
National Institute of Advanced Industrial Science and Technology (AIST), which was jointly and reorganized, and the economy that conducts research analysis and research on economic and industrial policies
The National Institute of Advanced Industrial Science and Technology (RIETI) can be mentioned. Of these, AIST became a "designated national research and development corporation" in 2016.
It is specified.
The Ministry of Economy, Trade and Industry also has the Japan Aerospace Exploration Agency JAXA and the Japan Agency for Medical Research and Development (AMED) with other ministries.
It is jointly under the jurisdiction.
(6) Other ministries
In addition to the Ministry of Education, Culture, Sports, Science and Technology and the Ministry of Economy, Trade and Industry, many ministries such as the Ministry of Health, Labor and Welfare and the Ministry of Agriculture, Forestry and Fisheries have announced that
Involved in vation. Every year, the Cabinet Office is involved in science and technology related to the government, including such related ministries and agencies.
The budget is tabulated and published.
According to it, the Ministry of Education, Culture, Sports, Science and Technology and the Ministry of Economy, Trade and Industry have budgeted for science and technology for the entire government (as of the beginning of 2019).
It accounts for nearly 70%.
In 2015, the Ministry of Foreign Affairs appointed a “Minister of Foreign Affairs Science and Technology Advisor”. The adviser is the Minister of Foreign Affairs
Support activities in terms of science and technology, and strengthen cooperation with science and technology advisors and stakeholders in the field of science and technology in each country
While doing so, he advises on the utilization of science and technology in the planning and drafting of various foreign policies.
(7) Headquarters established in the Cabinet
In recent years, in parallel with the system based on the Science and Technology Basic Law, the section that should be promoted comprehensively and intensively as a whole country
The basic law was enacted on the subject, and a headquarters was set up with the Prime Minister as the head and the relevant ministers as members.
The number of things to work on has increased. In science and technology, the Intellectual Property Strategy Headquarters, Umi, in relation to the Intellectual Property Basic Act
General Ocean Policy Headquarters based on the Western Basic Law, Space Development Strategy Headquarters based on the Basic Space Law, Advanced Information and Communication Network
Advanced Information and Communication Network Society Promotion Strategy Headquarters based on the Basic Law for Network Society Formation (IT Comprehensive Strategy Book)
Department), Health / Medical Strategy Promotion Headquarters based on the Health / Medical Strategy Promotion Law, etc. In July 2018
Is a cross-cutting and substantive of the Council for Science, Technology and Innovation and these headquarters, based on an integrated strategy.
The "Integrated Innovation Strategy Promotion Council" was established to make various adjustments and promote the integrated strategy.
Following the adoption of the Sustainable Development Goals (SDGs) by the United Nations, the Minister of State is a member.
The Sustainable Development Goals (SDGs) Promotion Headquarters was established in May 2016.
(8), National Institute for Materials Science, RIKEN
Tokoro, three corporations of National Institute of Advanced Industrial Science and Technology are designated as this corporation. CRDS-FY2019-FR-02 National Research and Development, Japan Science and Technology Agency Research and Development Strategy Center
Ten
[Chart I-4] A bird's-eye view of research funding agencies and competitive funding systems
JSPS: Japan Society for the Promotion of Science, JST: Japan Science and Technology Agency, NEDO: New Energy and Industrial Technology Development Organization,
AMED: Japan Agency for Medical Research and Development, SIP: Strategic Innovation Creation Program (Cabinet Office),
Moonshot R & D Program (Cabinet Office), COI: Center of Innovation (JST)
Source: R & D overview report "Transition of Japan's Science and Technology Innovation Policy-From the Enactment of the Science and Technology Basic Law to the Present-" (2020)
Research and Development Strategy Center)
The outline of the main funding organizations related to science and technology is as follows.
(1) Japan Society for the Promotion of Science (JSPS)
An independent administrative agency under the jurisdiction of the Ministry of Education, Culture, Sports, Science and Technology, established in 2003. Its predecessor was Japan, a foundation established in 1932.
This is the Japan Society for the Promotion of Science. Grants-in-Aid for Scientific Research (Grants-in-Aid for Scientific Research), etc. as a core institution responsible for the promotion of science in Japan
Implemented projects such as subsidizing academic research, providing funds for training researchers, and promoting international exchange related to academics.
doing. Kakenhi has reached over 200 billion yen annually, and JSPS is Japan's largest funding machine.
Seki.
(2) Japan Science and Technology Agency (JST)
Its predecessor was the Japan Science and Technology Information Center, which was established in 1957, and the New Technology Development, which was established in 1961.
It is a special corporation science and technology promotion corporation established in 1996 with the business corporation as the parent body. Science and Technology Basic Plan
As a core executing agency, we are implementing projects that contribute to the creation of science and technology innovation.
R & D bird's-eye view report
R & D strategies of major countries (2020)
CRDS-FY2019-FR-02 National Research and Development, Japan Science and Technology Agency Research and Development Strategy Center 11 Japan
The strategic creative research promotion project, which is the core of funding, aims to achieve the strategic goals set by the government.
Promote problem-achieving basic research and create innovative technology seeds that generate science and technology innovation
The purpose is to make it. In the future society creation business, economic and social needs are taken into consideration.
Set technically challenging goals with a clear view of targets (exit) that have an impact on
However, it can be put into practical use by utilizing promising results such as strategic creative research promotion projects and scientific research funding subsidies.
We are conducting research and development aiming at the stage where it can be determined whether or not it is possible (proof of concept: POC).
(3) National Research and Development Corporation New Energy and Industrial Technology Development Organization (NEDO)
Its predecessor was the New Energy and Industrial Technology Development Organization, which was established in 1980. Japan's largest public R & D machine
As a screwing organization, it plays a part in economic and industrial administration, "solving energy and environmental problems" and "industry".
We are working on two missions, "strengthening industrial technology."
(4) Japan Agency for Medical Research and Development (AMED)
From April 2015, conduct research and development in the medical field, improve the environment, and provide subsidies.
Established as the Japan Agency for Medical Research and Development. Health / Medical Strategy Promotion Headquarters Measures
Based on the established medical field R & D promotion plan, we will focus on nine collaborative fields such as regenerative medicine and cancer.
Promotion of consistent research and development from the basics to practical application in the medical field, smooth practical application of results, and medical field
It is supposed to comprehensively and effectively improve the environment for research and development. __ Industry-academia collaboration / regional promotion, 1) Large-scale radiation facility (SPring-8), 2) X-ray free electron laser facility (SACLA), 3) Supercomputer "K computer", 4) High-intensity proton accelerator facility (J- Four PARC) facilities have been designated and are supported by the government.
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Physical and Mathematical Sciences
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Biological Sciences
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Engineering and Applied Sciences
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Biomedical Sciences
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Behavioral and Social Sciences
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Applied Biological, Agricultural, and Environmental Sciences
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National Academy of Sciences
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Japan Academy
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Royal Society
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Prussian Academy of Sciences
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French Academy of Sciences
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Royal Swedish Academy of Sciences
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Russian Academy of Sciences
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Royal Netherlands Academy of Arts and Sciences
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External link
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SCIENCES
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Nature
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National Science Foundation
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NASA NSAS
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• National Medal of Science
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• Alan T. Waterman Award
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• Vannevar Bush Award
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National Science Foundation
AAAS American Association for the Advancement of Science
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Office of Science and Technology Policy (OSTP) https://www.whitehouse.gov/ostp/
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National Science Foundation (NSF) https://www.nsf.gov/
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National Institutes of Health (NIH) https://www.nih.gov/
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Social Science Research Council (SSRC) https://www.ssrc.org/
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The National Academies of Sciences, Engineering, and Medicine (NAS)
Genetic diagnosis
• Gene polymorphisms (SNPs)
• Infection Disease
• Personal identification (Human ID)
• Cancer-related genes (Oncology)
• Animals (small animals / industrial animals) / plants (Animal / Plant)
• Food safety (detection of food poisoning bacteria)
• Environmental inspection (environmental microbial analysis)
• Immunoassay diagnosis
• allergy
• Food allergens
• Autoimmunity
• Tumor marker
• Bacterial typing
• Biochemical diagnosis
• Small animal diagnosis
• Bedside diagnostics
Medical / Life Science, Robot / Mobility / Space DX / Service / Platform Environment / Energy / Social Clean Tech SDGs, etc.
Development of diagnostic imaging support AI specialized for endoscopes.
• Clinicians “miss lesions” and “massive doubles”
Solving on-site problems such as "check"
Founded for. The University of Tokyo Hospital, Keio University Hospital, Cancer Institute
Conducted joint research with major hospitals such as Ariake
Improved the accuracy of AI image diagnosis.
• Japan's flexible endoscopes have the world's largest share of equipment
With 98%, the skill of specialists is the best in the world, and AI diagnosis
To the top level.
Innovate medical care using data and technology.
• Many online medical services are available nationwide
Introduced to medical institutions. Online medication instruction
We also provide services. Tokyo doctor as a measure against corona
Adopted by teachers' associations.
• Support for clinical development of pharmaceutical products and digital therapy
This in line with the development of tics and the evolution of medical care
Develop new insurance products that have never been seen before.
• The management team is a doctor and strategic consultant, Ph.D. at Herbert University, Ph.D. at Oxford University, Ph.D. in Cambridge University.
People from lines, etc.
Has a highly controlled and uniform sugar chain structure
Manufactures biopharmacy. (What is a sugar chain?
Third life chain after nucleic acids and proteins)
• Based on the technology cultivated through joint research with Osaka University
In addition, cheap and high-quality sugar chains to the pharmaceutical industry
Provided. Sustained drug effect, allergic reaction
Decrease, targeting to specific organs / cells
Possibility of application to treatment of infectious diseases.
VLP vaccine (no viral gene)
Therefore, it only pulls the immune response without infection.
Wake up. Safe and overwhelmingly effective with a small amount)
Development of new drug by.
• Excitement for new coronavirus infections
Chin with the support of public institutions such as AMED
However, it is under research and development.
• Vaccines for infectious diseases such as malaria and dengue
Also developed a vaccine for the treatment of cancer.
Practical application of "flying car", future Mobi
Aiming to contribute to the Liti society, aircraft
Drone and automobile engineer are one
"Flying car" and "Logistics draw"
Developed.
• “Driving the once-in-a-century Mobility Revolution
"Ru" is listed in the mission.
Solving the problems of labor shortage and aging in agriculture
Automatic harvesting of agricultural products using AI
Developed a bot.
• “Achieving sustainable agriculture that will last 100 years
With the vision of "Ru", "Agriculture with technology"
"Solving business issues" is our mission
NS.
Constellation with high-performance small radar satellite
Form and generate rations (satellite groups)
Analysis solution using data and AI
Provide.
• Apply the results of the Cabinet Office Impact program.
Commercialized for disaster response and infrastructure development.
• “People with new data and technology
"Learning" that expands the possibilities of
"Realization of the world" is the mission.
Research and development and manufacturing of space work robots.
• Work inside and outside the space station, in orbit
Service (refueling / repairing satellites, fat
Outboard robot capable of removal service)
Arms, lunar exploration and base development work
Aim to robotize general-purpose work in the area.
• “Providing a cheap and safe way of working in space
”Is a vision.
DX recommendation of site management and process management in the construction industry
Susumu.
• Separately managed in the office and on-site
Centralized management of photos and drawings in the cloud. vinegar
Complete office work on-site with Maho App
Done.
• Look at the platforms of the global construction industry
Mark.
• Are you an investor, such as receiving investment from overseas?
Also highly evaluated (cumulative funding amount is about 87 in total
100 million yen).
Promote digital transformation of government services.
• Register copy / seal certificate for business operators
Online billing services and autonomy
All administrative procedures for the body and government offices
Digital line that can be completed with a smartphone
Deploying political platform services.
• Mainly Sapporo, Yokohama, Kobe, Fukuoka, etc.
Used by many government agencies including local governments.
• Co., Ltd. for AI technology research
It is supposed to be incept.
Match the time you want to work and the time you want to work
Exhibition of ching gap bite service
Open.
• "Working style" is updated according to the times
Raise the potential workforce by
And aim to realize the solution of social issues.
• Being able to work immediately without a resume or interview
You can receive money immediately after work
Services that can be done.
• Founder Kokuryu started his business while attending university, and became a business in August 2018.
Is it a financial institution since the service release of the month?
The total amount raised, including their borrowings, is about 9 billion yen.
A company that provides AI-equipped IP phones
Support for improving the productivity of the industry.
• AI transcribes and analyzes phone calls
And it automatically works with the customer management system. education
Supporting self-coaching and sales
Contributes to improving the reduction rate.
• “Reinventing communication, people
The mission is to create a society that thinks about people.
New alternative to plastic and paper from limestone
Developed material,
Recycled material CirculeX exhibits resource recycling business
Open.
• Products using new materials are available at Haneda Airport and Yodobashi
Camera bags, Yoshinoya menu tables, etc.
Adopted by more than 6,000 companies and organizations. Municipality and
Material resai of new materials to work with companies
There are many cases of Kuru and resource recycling.
• Use limestone with low risk of depletion and use life support
Control CO2 emissions throughout the vehicle, globally
Aiming to realize a "sustainability revolution"
Development, production and sales of vegetable meat (miracle meat).
• Germinate with patented technology "Ochiai high pressure method"
Developing "Miracle Meat" using soybeans
Cormorant.
• Ajinomoto, Nichirei Foods, Marubeni, Marui Group
With 15 major domestic food manufacturers and trading companies
Implemented this business alliance. "All Japan concept"
And work on the spread of vegetable meat.
• Plant meat is the fourth meat after "beef," "pork," and "bird."
Sustainable by becoming a natural world
We will contribute to the realization of a new society.
People in non-electrified areas using IoT technology
Energy as a to provide electricity services to
Services (EaaS) Business development.
• Work with mobile money, which is widespread in Africa
We built a billing system and charged it with sunlight.
We offer prepaid rental of LED lanterns.
• Service operations are carried out at kiosks (retail stores) in each village.
Kiosk that goes through and increases every day
Exhibition of new services utilizing networks
Open.
• “Solving social issues through business,
The mission is to "empower people"
Small business loans for low-income earners in developing countries
Shareholding association of companies implementing "microfinance"
As a company, funding, strengthening governance, tech
Expanding financial access through the introduction of Nology
contribution.
• India, Cambodia, Sri Lanka, Myan
Mar has more than 5,500 group employees and is a consultant
The number of customers is 750,000, and the loan balance is 42.8 billion yen (August 2021)
As of the month). Good financial services by 2030
The goal is to reach more than 100 million people in 50 countries.


Health management company
DX all employees doctoral technical professional
GDM SDGs
Product R & D ---> Product Planning ---> New Product R & D
Patented proprietary technology
Electric bicycle EV technology Utilizing digital technology
Energy FCV HV PHV Utilizing digital technology
customer
Hino Isui Toshiba Hitachi Panasonic Mitsubishi GM
Joint research and development with Yasukawa Honda, Toyota, Nissan, Sumitomo Electric, etc.




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Top 10 scientists worldwide in ours Team
Among them, the familiar statistical machine learning man Michael I. Jordan ranked 4th, and the deep learning gods and the 2018 Turing Award winners Geoffrey Hinton and Yoshua Bengio ranked 9th and 10th respectively.
In addition, there are two Chinese scholars among the top 10 computer scientists, namely Jiawei Han, professor of computer science at the University of Illinois at Urbana-Champaign, and Philip S. Yu, professor of information technology at the University of Illinois at Chicago.






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We support the decarbonization of the world. I will tell you about the importance of climate change measures such as efforts related to environmental measures.
• Decarbonization
• AI
• Collaborative creation
• Decarbonization
• SDGs
• Renewable energy
"Change to a carbon-free society is a new business opportunity" What are the climate change measures required of companies?
• Decarbonization
• SDGs
• Renewable energy
The following three are exhibited as the only one and number one decarbonization technology that supports the realization of "2050 carbon neutral" and the decarbonization of the world.
• ・ Waste plastic recycling technology (on-the-job / online)
• ・ CO2 separation and recovery technology HiPACT® / DDR zeolite membrane (online)
• ・ Solution for realizing a hydrogen-based society AMUSE® (online)
Collaborative research between Hitachi and our company Development of "monitoring system" to prevent illegal logging in tropical rainforests
• As the “EARTH FOOD CREATOR Nissin Foods Group,” which constantly imagines new food cultures, the Nissin Foods Group aims to solve environmental and social issues. Its representative brand, "Cup Noodles," has been constantly evolving since it was born in Japan in 1971 as the world's first cup noodles. Currently, various technologies and ingenuity for solving environmental and social issues in small products such as the use of containers with a biomass content of 80% or more, the utilization of plant-derived meat substitute technology, and the sustainable procurement of palm oil. It is packed with and delivered to consumers with deliciousness. Under the NISSIN FOODS Group and our collaborative environmental strategy "EARTH FOOD CHALLENGE 2030", effective use of resources and SBT-certified CO2 reduction target (Scope 1 + 2_ vs. 2018 ▲ 30%, Scope 3_ vs. 2018 We will continue to actively tackle environmental issues with the aim of achieving a ratio of ▲ 15%).
The use of hydrogen fuel cells is the most suitable solution for the realization of an energy dispersive society
Tokyo 2020 athlete village site "HARUMI FLAG"
RE100 factory
Utilization of renewable energy is indispensable for the realization of carbon neutrality. However, since renewable energy is an unstable power source, energy storage means are required to adjust supply and demand. Therefore, we are exhibiting a system that can meet small to large-scale energy demand with fuel cells that utilize hydrogen.
At the exhibition
① Supply hydrogen to buildings and residential areas through pipelines
(2) Transport, store and utilize hydrogen to high demand areas
③ Utilize by-product hydrogen generated from chemical factories, etc.
(4) Distributed power source that produces electricity from renewable energy and produces hydrogen from that electricity to utilize it We introduce various methods of utilizing hydrogen using a diorama.
EcoPro Online 2020
Pure hydrogen fuel cell
The future of the earth pioneered by hydrogen
The hydrogen society that Panasonic and our company are aiming for is a society where people can live comfortably without emitting CO2 by locally producing and consuming energy. The city starts to move with hydrogen. Panasonic's pure hydrogen fuel cell supports this.
feature
High power generation efficiency, instant start-up, and power supply even in the event of a power outage
• Achieves the industry's highest power generation efficiency of 56% with an output of 5 kW * 1. We meet the power generation needs of our customers.
* 1 As of October 2020, research
• Can be started in 1 minute. It is useful for peak cuts that require quick response. Also, in the event of a power outage, it is possible to generate electricity using only hydrogen. Contribute to BCP (Business Continuity Plan).
Can be connected to meet various output requests
• By connecting multiple units, it is possible to handle from home use to store to industrial use.
Utilization material HEMIX ™ bioplastic
Chemical recycling technology that realizes resource recycling of plastics
Providing three chemical recycling technologies, monomerization, oiling, and gasification, according to the degree of mixing of waste plastic and impurities. Recycling technology for the right person in the right place
Monomerization: The DMT method is an effective method for recycling clothing polyester and cascade-recycled PET products, which have an advantage in removing dyes and impurities in raw materials and are not suitable for material recycling. We have a track record of commercial scale operations and solve the problem of mass disposal of clothing.
Oil conversion: A technology based on the largest commercial oil conversion equipment in Japan, which uses a catalytic pyrolysis method. Pyrolysis oil is supplied to refineries and chemical plants to realize chemical recycling. Unlike general oleochemical technology, it is possible to treat PVC / PET mixed plastics.
Gasification: EUP gasifies waste plastic by partial oxidation to produce syngas that can be used to synthesize chemicals such as ammonia and olefins. It has the world's only long-term commercial operation record for gasification chemical recycling applications.
Using these three technologies, we can propose processing processes tailored to raw materials and provide various services in the plant life cycle of business planning (raw material procurement / product sales) / license / plant construction / maintenance operation.
Next-generation aviation fuel (SAF) using spent cooking oil
JGC Group and our collaborative research will collaborate with Revo International Co., Ltd. and Cosmo Oil Co., Ltd. to hydrogenate used cooking oil and build a supply chain to produce domestically produced SAF (next-generation aviation fuel). We are also working on it. By promoting the domestic production of SAF, which is already in practical use in Europe and the United States, we will contribute to the decarbonization of the domestic aviation industry.
Spread of renewable energy and circular economy by self-consumption solar power generation system
The trump card for the spread of renewable energy! Introduction of development products and business development associated with self-consumption type photovoltaic power generation system
Image of installing solar power generation equipment on the roof and parking space
Inspection of used solar cell module (By visualizing the infrared rays emitted from the cell when an electric current is passed through the solar cell module, the cell is checked for cracks and wiring abnormalities.)
We believe that a "self-consumption photovoltaic power generation system *" that enables the mass introduction of renewable energy is an effective means as a countermeasure against climate change, which is approaching the time limit. (* Hereafter, self-consumption system) The self-consumption system refers to the idea of self-production and self-consumption of electricity, in which solar power generation equipment is installed at home or in-house and the electricity generated there is used by ourselves. Based on the four keywords of "cheap," "mass," "freedom," and "fast," we are developing products and developing businesses that accompany self-consumption systems. In addition, we have been working on the problem of disposal of solar cell modules, which is inevitable due to mass introduction, since 2005, ahead of other companies. We have inspected 140,000 waste modules so far, and based on the vast amount of data, knowledge, and know-how that we have accumulated, we are working to build an appropriate recycling product cycle rather than simply introducing a large amount. increase.
JAXA Japan Aerospace Exploration Agency and our collaborative research satellite climate change observation efforts
As a core institution for developing Japanese artificial satellites, we are promoting earth observation research and contributing to climate change response.
Figure 1. Earth observation satellite operated by JAXA
Figure 2. JAXA Earth Observation Satellite Contribution to ECV
JAXA develops and operates earth observation satellites capable of observing land, ocean, and atmosphere, and contributes to responding to global issues such as disasters and climate change. Currently, we operate six earth observation satellites, and the observation data obtained from these satellites is used by people all over the world and is open to the public free of charge so that it can be used to solve various problems on the earth.
In order to grasp the situation of climate change, it is necessary to observe various environmental factors "face-to-face", "globally" and "regularly" and extract changes. Contributed to the observation of 26 ECVs among the Essential Climate Variables (ECVs) established internationally for the purpose of concretely and accurately grasping and predicting changes in the global environment due to climate change. I am. Long-term observation data can grasp changes in the global environment due to climate change, and is used in various reports such as the IPCC.
Disseminate the world's only tropical peatland management model to the world with the world's most advanced observation technology and satellite utilization technology
We will contribute to climate change countermeasures by maximizing the original value of tropical peatlands using the world's only know-how and cutting-edge technology.
A tropical peatland reserve managed by Sumitomo Forestry and our company in Indonesia
Concept of tropical peatland management utilizing meteorological observation technology
Tropical peatlands and forests store vast amounts of carbon and conserve the Earth's water cycle and biodiversity. However, overdevelopment and fires are said to have an annual CO2 emission of 2.2 to 3.7 billion tons (equivalent to 6 to 11% of the world's emissions), affecting global climate change. Constructed a water storage type management model in a degraded forest of about 140,000 ha in Indonesia. Accumulate field data for more than 10 years and implement sustainable forest management based on scientific knowledge. Sumitomo Forestry's know-how is combined with IHI's cutting-edge technologies related to satellite, UAV, and meteorological observation. By observing from the sky, monitoring from the ground, and AI analysis, we will provide management technology to disseminate a sustainable tropical peatland management model all over the world and contribute to global climate change countermeasures. The Ministry of Economy, Trade and Industry is promoting the use of satellite data such as HISUI, ASTER, and PALSAR, and is supporting the development and worldwide dissemination of this project. In the future, the government, academia and the private sector will aim to improve the observation by satellites in the equatorial orbital region where the world's tropical peatlands can always be observed.
Solution to realize a hydrogen society AMUSE®︎
Possibility of ammonia as a hydrogen carrier
Green Ammonia Value Chain Demonstration
This is a value chain demonstration that uses green hydrogen derived from renewable energy (photovoltaic power generation) to produce green ammonia, and then uses that ammonia to achieve CO₂-free power generation using an ammonia gas turbine.
Development of green hydrogen / ammonia plant design optimization tool
Renewable energies such as solar power and wind power have different profiles depending on the region and season, and are constantly changing.Therefore, appropriate equipment specifications and capacity design are required for each equipment. Developed.
As a trump card for the realization of a carbon-free society, hydrogen energy is expected to expand its use in the future. It can handle all three major hydrogen carriers (liquefied hydrogen, organic hydride, and ammonia) that are expected to become widespread in the future, and has a great advantage in utilizing hydrogen carriers and ammonia as fuel. We are developing our own solution AMUSE®︎ and bringing together a wide range of technologies inside and outside the company, aiming for the early realization of a hydrogen-based society.
At this exhibition, we will introduce the world's first successful value chain demonstration of green ammonia and the development of an optimum setting tool that responds to fluctuations in renewable energy.
Hydrogen gas turbine technology in collaboration with Mitsubishi Heavy Industries and our company We will contribute to the realization of a carbon-neutral society. The large-scale use of hydrogen in gas turbines creates a virtuous cycle of reducing costs and reducing CO2 emissions throughout the hydrogen supply chain.
Conceptual diagram of hydrogen gas turbine and trial calculation result of hydrogen utilization
Zero Carbon Humber / H2H Saltend project overview
We are working on the development of hydrogen gas turbine technology based on the world's highest level of efficiency and reliability of large gas turbine technology. Utilizing our abundant track record and experience of using hydrogen-rich fuel for power generation for half a century, we have already achieved 30% hydrogen co-firing based on existing combustion technology for large gas turbines with low NOₓ and high efficiency. ..
Furthermore, a new combustion method is under development for 100% hydrogen combustion, and it is about to be realized. This combustion method solves the problems caused by the high combustion speed peculiar to hydrogen, and can be applied by making minimal modifications to existing power plant equipment. For example, in the United Kingdom, we are participating in the Zero Carbon Humber project, which aims to decarbonize the large-scale industrial cluster Humber, and are conducting technological studies to convert the Salt end power plant in the area from natural gas to hydrogen.
To realize the world's most efficient hydrogen gas turbine
Strategies for the Realization of a Sustainable Decarbonized Society in Developing Countries
"Promotion of implementation of the Paris Agreement" as a climate change strategy for developing countries
We advocate "promotion of co-benefits-type climate change countermeasures".
In implementing the global agenda
Priority Challenges for Climate Change Countermeasures (Decarbonized and Climate Change-Resistant Urban Development / Infrastructure Investment, Climate Change Policy / Institutional Improvement)
In implementing the global agenda
Priority Challenges for Climate Change Countermeasures (Climate Risk Assessment and Strengthening Adaptation Measures, Conservation of Forests and Natural Ecosystems)
JICA and our company have more than 100 bases in developing countries as JICA Japan's development assistance organization, and provide support that combines (1) loan aid, (2) grant aid, and (3) technical cooperation. In June 2021, the "Global Agenda (Climate Change)" was formulated as a business strategy for climate change countermeasures. We have set up two pillars of our business to realize a society that is decarbonized and resilient to climate change in developing countries.
1. 1. Promotion of implementation of the Paris Agreement
Support for planning and updating climate change countermeasures such as "full implementation of NDC", "monitoring, report formulation" and "long-term strategy formulation" in developing countries
2. Promotion of co-benefits-type climate change measures
Contributing to the achievement of the SDG at the same time as promoting climate change mitigation measures and adaptation measures in the following three areas of strength.
(1) Promotion of urban development and infrastructure development that is low-carbon and decarbonized and resistant to climate change
(2) Strengthening adaptation measures and risk finance based on climate risk assessment
(3) Reduction of GHG emissions and promotion of absorption through strengthening conservation and management of forests and natural ecosystems
Environmentally friendly concrete with CO² emissions of zero or less "CO²-SUICOM"
"CO²-SUICOM" is a technology that absorbs carbon dioxide in the process of solidifying concrete and fixes it semi-permanently.
CO²-SUICOM is a technology that can contribute to the reduction of CO² emissions of approximately 300 kg / m³ or more during general concrete manufacturing. Specifically, (1) By replacing more than half of the cement with industrial waste or a special admixture that utilizes industrial waste that emits zero CO² as part of the raw material, the CO² emitted during cement manufacturing can be significantly reduced. (Reduction amount: approx. 200 kg / m³), and by curing concrete using this special admixture in a high-concentration CO² environment (carbonation curing), a large amount of CO² is absorbed and fixed to the concrete. (Absorption amount: Approximately 100 kg / m³). According to various research organizations (Mckinsey, etc.), concrete absorption and fixing technology for minerals including CO²-SUICOM is expected to contribute to CO² reduction of about billions of tons as of 2030, and emissions throughout Japan. It has the potential to exceed the amount.
CO²-SUICOM is the world's first successful commercialized technology to reduce CO² emissions during concrete production to virtually zero or less.
In Japan, it has already been used for construction of the Tokyo Gaikan Expressway and paved roads, etc., and we are proceeding with commercialization overseas. For the purpose of contributing to a carbon-free society, Chugoku Electric Power Co., Inc., Kajima Corporation, Denka Landes, and Mitsubishi Corporation are in charge of technology, and Mitsubishi Corporation is mainly in charge of commercialization overseas.
CO²-SUICOM technology makes it possible to reduce CO² with one concrete block, which is equivalent to one year's worth of cedar trees. Realizing the world's sustainable society by transforming the common sense of concrete, which is one of the most consumed materials in the world, and decarbonizing infrastructure and urban development around the world with the power of CO²-SUICOM. I think that I want to do it.
Chugoku Electric Power Co., Inc.
Kajima Corporation
Denka Co., Ltd.
Landes Co., Ltd.
Collaboration with Mitsubishi Corporation
Collaborative research and development with Seven & i
Open innovation through co-creation with Seven & i business partners
-Challenge to carbon neutral and circular economy
Environmental Declaration "GREEN CHALLENGE 2050"
The Environmental Declaration "GREEN CHALLENGE 2050" sets the goal of reducing CO2 emissions associated with the operation of the Group's stores by 50% by 2030 (compared to FY2013) and virtually zero by 2050. It is difficult for us to achieve our goals by ourselves, and we are promoting open innovation initiatives through co-creation with our business partners.
Of these, (1) 100% renewable energy store initiatives that utilize reused batteries and original storage batteries for electric vehicles, and (2) PET bottle collection / recycling initiatives that use recovery machines that can also be installed at convenience stores.







Guo Long
Computer Science
Visiting Professor of Tsinghua University
Professor, IEEE Fellow
Associate Chair
NSFC Distinguished Young Scholar
Top Computer Science Scientists
https://research.com/scientists-rankings/computer-science/2021
Director of Tsinghua-CAE Joint Research Center for Knowledge & Intelligence
Knowledge Engineering Group (KEG),
Department of Computer Science,
oxford University
CONTACT
Office: Oxford, OX1 2JD, United Kingdom, LCFI research Lab
University of Oxford
United Kingdom
Top Computer Science Scientists
Andrew Zisserman research Lab
University of Oxford
United Kingdom
Visiting Professor of Tsinghua University
1-308, FIT Building, Tsinghua University, Beijing, 100084. China PR.
E-Mail: 1500467240@qq.com
https://www.aminer.cn/profile/54591fa2dabfaeb0fe308f65
I am a Full Professor and the Associate Chair of the Department of Computer Science and Technology of oxford University. I obtained my Ph.D. Rhodes Scholarship Clarendon Fund scholarships Pacific Alliance Oxford Scholarships in DCST Visiting Professor of of Tsinghua University in 2006. My research interests include artificial intelligence, data mining, social networks , machine learning and knowledge graph, with an emphasis on designing new algorithms for mining social and knowledge networks.
2017 - The Royal Society Milner Award In recognition of his exceptional achievements in computer programming which includes work on computational theory and commercial systems for geometrical images.
2008 - BMVA Distinguished Fellow
2007 - Fellow of the Royal Society (UK) In recognition of his exceptional achievements in computer programming which includes work on computational theory and commercial systems for geometrical images
I have been visiting scholar at Cornell University (working with Prof. John Hopcroft and Jon Kleinberg), University of Southampton (working with Dame Wendy Hall), KU Leuven (working with Marie-Francine Moens), University of Illinois at Urbana-Champaign (short term, working with Jiawei Han), Chinese University of Hong Kong (working with Jeffrey Yu), and Hong Kong University of Science and Technology (working with Qiong Luo). During my graduate career, I have been an intern at NLC group of Microsoft Research Asia from 2004 to 2005. I also have attended the internship program of IBM China Research Lab in 2004.
I have published more than 200 journal/conference papers and hold 20 patents. I served as PC Co-Chair of CIKM’16, WSDM’15, Associate General Chair of KDD’18, and Acting Editor-in-Chief of ACM TKDD, Editors of IEEE TKDE, IEEE TBD, and ACM TIST. I am leading the project AMiner.org for academic social network analysis and mining, which has attracted more than 10 million independent IP accesses from 220 countries/regions in the world. I was honored with the UK Royal Society-Newton Advanced Fellowship Award, CCF Young Scientist Award, NSFC for Distinguished Young Scholar, and KDD’18 Service Award.
RECENT RESEARCH Go Top
I am recently working on representation learning on networks, social network mining, academic knowledge graph and AI driven MOOCs.
Representation Learning on Networks [GNN&Self-supervised Learning] [HPC Online Talk on GNN & Reasoning] [ADL Online Talk on GNN & Reasoning] [GNN&Cognitive Graph] [Cognitive Graph] [GNN&Reasoning] [Talk at Brain-and-AI] [Talk at WeBank] [Keynote at CNCC'19 Forum] [Keynote at ASONAM'19] [Keynote at KDD'19 DL Day] [Keynote at KDDFeed'19] [Talk at KDD China'19] [Tutorial at WWW'19] [Tutorial]

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Chinese Academy of Sciences
SELECTED PUBLICATIONS (A COMPLETE LIST) Go Top
Social Network / Data Mining / Machine Learning
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Guo Long ,Shu Zhao, Ziwei Du, Jie Chen, Yanping Zhang, Jie Tang, and Philip S. Yu. Hierarchical Representation Learning for Attributed Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted).
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Guo Long ,Zhenyu Hou, Yukuo Cen, Yuxiao Dong, Jie Zhang, and Jie Tang. Automated Unsupervised Graph Representation Learning. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted).
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Guo Long ,Zhengxiao Du, Chang Zhou, Jiangchao Yao, Teng Tu, Letian Cheng, Hongxia Yang, Jingren Zhou, and Jie Tang. CogKR: Cognitive Graph for Multi-hop Knowledge Reasoning. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF]
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Guo Long ,Jie Gong, Xiao Liu, and Jie Tang. How Monetary Incentives Improve Outcomes in MOOCs: Evidence from a Field Experiment. Journal of Economic Behavior and Organization (JEBO), 2021 (accepted). [PDF]
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Guo Long ,Xiao Liu, Fanjin Zhang, Zhenyu Hou, Li Mian, Zhaoyu Wang, Jing Zhang, and Jie Tang. Self-supervised Learning: Generative or Contrastive. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [Arxiv] [*Slides*]
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Guo Long ,Da Yin, Weng Lam Tam, Ming Ding, and Jie Tang. MRT: Tracing the Evolution of Scientific Publications. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [Slides_pdf] [Slides_pdf] [*System*]
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Guo Long ,Xu Zou, Da Yin, Qingyang Zhong, Hongxia Yang, Zhilin Yang, and Jie Tang. Controllable Generation from Pre-trained Language Models via Inverse Prompting. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF] [*Code&Data&Model*] [*Demo*]
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Guo Long ,Xu Zou, Qinkai Zheng, Yuxiao Dong, Xinyu Guan, Evgeny Kharlamov, Jialiang Lu, and Jie Tang. TDGIA: Effective Injection Attacks on Graph Neural Networks. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF]
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Guo Long ,Qingsong Lv, Ming Ding, Qiang Liu, Yuxiang Chen, Wenzheng Feng, Siming He, Chang Zhou, Jian-guo Jiang, Yuxiao Dong, and Jie Tang. Are we really making much progress? Revisiting, benchmarking and refining the Heterogeneous Graph Neural Networks. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF] [Slides_pdf] [*Code&Data*] [Leaderboard]
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Guo Long ,Tinglin Huang, Yuxiao Dong, Ming Ding, Zhen Yang, Wenzheng Feng, Xinyu Wang, and Jie Tang. MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF] [*Code*]
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Guo Long ,Junyang Lin, Rui Men, An Yang, Chang Zhou, Yichang Zhang, Peng Wang, Jingren Zhou, Jie Tang, and Hongxia Yang. M6: Multi-Modality-to-Multi-Modality Multitask Mega-transformer for Unified Pretraining. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF]
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Guo Long ,Yuxuan Shi, Gong Cheng, Trung-Kien Tran, Jie Tang, and Evgeny Kharlamov. Keyword-Based Knowledge Graph Exploration Based on Quadratic Group Steiner Trees. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI'21). [PDF] [*Code*]
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Guo Long ,Jiezhong Qiu, Laxman Dhulipala, Jie Tang, Richard Peng, and Chi Wang. LightNE: A Lightweight Graph Processing System for Network Embedding. In Proceedings of the 2021 ACM SIGMOD international conference on Management of data (SIGMOD'21), 2021. [PDF] [Slides_ppt] [Slides_pdf] [*Code*]
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Xiao Liu, Li Mian, Yuxiao Dong, Fanjin Zhang, Jing Zhang, Jie Tang, Peng Zhang, Jibing Gong, and Kuansan Wang. OAG_know: Self-supervised Learning for Linking Knowledge Graphs. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021. [PDF] [*Data*] [*Code*]
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Guo Long ,Xu Han, Zhengyan Zhang, Ning Ding, Yuxian Gu, Xiao Liu, Yuqi Huo, Jiezhong Qiu, Liang Zhang, Wentao Han, Minlie Huang, Qin Jin, Yanyan Lan, Yang Liu, Zhiyuan Liu, Zhiwu Lu, Xipeng Qiu, Ruihua Song, Jie Tang, Ji-Rong Wen, Jinhui Yuan, Wayne Xin Zhao, and Jun Zhu. Pre-Trained Models: Past, Present and Future. AI Open Journal, 2021. [PDF]
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Guo Long ,Xueyi Liu and Jie Tang. Network Representation Learning: A Macro and Micro Outlook. AI Open Journal, 2021. [PDF] [Slides]
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Guo Long ,Fanjin Zhang, Jie Tang, Xueyi Liu, Zhenyu Hou, Yuxiao Dong, Jing Zhang, Xiao Liu, Ruobing Xie, Kai Zhuang, Xu Zhang, Leyu Lin, and Philip S. Yu. Understanding WeChat User Preferences and “Wow” Diffusion. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021. [PDF] [Slides_ppt] [Slides_pdf] [*Code*] [*Data*]
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Guo Long ,Wenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han, Huanbo Luan, Qian Xu, Qiang Yang, Evgeny Kharlamov, and Jie Tang. Graph Random Neural Networks for Semi-Supervised Learning on Graphs. In Proceedings of the Thirty-Forth Annual Conference on Neural Information Processing Systems (NIPS'20). [PDF] [Appendix] [*Code*]
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Guo Long ,Ming Ding, Chang Zhou, Hongxia Yang, and Jie Tang. CogLTX: Applying BERT to Long Texts. In Proceedings of the Thirty-Forth Annual Conference on Neural Information Processing Systems (NIPS'20). [PDF] [*Code*] [*Data*]
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Guo Long ,Jiezhong Qiu, Chi Wang, Ben Liao, Richard Peng, and Jie Tang. A Matrix Chernoff Bound for Markov Chains and its Application to Co-occurrence Matrices. In Proceedings of the Thirty-Forth Annual Conference on Neural Information Processing Systems (NIPS'20). [PDF] [Slides_ppt] [Slides_pdf]
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Guo Long ,Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, and Jie Tang. Modelling High-Order Social Relations for Item Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2020 (accepted). [PDF]
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Guo Long ,Bo Chen, Jing Zhang, Jie Tang, Lingfan Cai, Zhaoyu Wang, Shu Zhao, Hong Chen, and Cuiping Li. CONNA: Addressing Name Disambiguation on The Fly. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2020 (accepted). [PDF]
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Guo Long ,Jiezhong Qiu, Qibin Chen, Yuxiao Dong, Jing Zhang, Hongxia Yang, Ming Ding, Kuansan Wang, and Jie Tang. GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training. In Proceedings of the Twenty-Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'20). [PDF] [Slides_ppt] [Slides_PDF] [*data & code*]
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Guo Long ,Zhen Yang, Ming Ding, Chang Zhou, Hongxia Yang, Jingren Zhou, and Jie Tang. Understanding Negative Sampling in Graph Representation Learning. In Proceedings of the Twenty-Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'20). [PDF] [Slides_ppt] [Slides_PDF] [*data & code*]
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Guo Long ,Yukuo Cen, Jianwei Zhang, Xu Zou, Chang Zhou, Hongxia Yang, and Jie Tang. Controllable Multi-Interest Framework for Recommendation. In Proceedings of the Twenty-Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'20). [PDF] [*data & code*]
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Guo Long ,Jibing Gong, Shen Wang, Jinlong Wang, Hao Peng, Wenzheng Feng, Dan Wang, Yi Zhao, Huanhuan Li, Jie Tang, and Philip Yu. Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View. In Proceedings of the 43th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'20). [PDF]
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Guo Long ,Yuxiao Dong, Ziniu Hu, Kuansan Wang, Yizhou Sun and Jie Tang. Heterogeneous Network Representation Learning. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI'20). [PDF] [Slides_PPT] [Slides_PDF] [Poster]
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Guo Long ,Jifan Yu, Gan Luo, Tong Xiao, Qingyang Zhong, Yuquan Wang, wenzheng feng, Junyi Luo, Chenyu Wang, Lei Hou, Juanzi Li, Zhiyuan Liu and Jie Tang. MOOCCube: A Large-scale Data Repository for NLP Applications in MOOCs. In Proceedings of the 58th Annual Meeting of the Association of Computational Linguistics (ACL'20). [PDF] [*data & code*]
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Guo Long ,Si Zhang, Hanghang Tong, Jie Tang, Jiejun Xu, and Wei Fan. Incomplete Network Alignment: Problem Definitions and Fast Solutions. ACM Transactions on Knowledge Discovery from Data (TKDD), 2020, accepted. [PDF]
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Guo Long ,Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang, and Jie Tang. Cognitive Graph for Multi-Hop Reading Comprehension at Scale. In Proceedings of the 57th Annual Meeting of the Association of Computational Linguistics (ACL'19). [PDF] [*data & code*]
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Guo Long ,Jifan Yu, Chenyu Wang, Gan Luo, Lei Hou, Juanzi Li, Jie Tang, and Zhiyuan Liu. Course Concept Expansion in MOOCs with External Knowledge and Interactive Game. In Proceedings of the 57th Annual Meeting of the Association of Computational Linguistics (ACL'19). [PDF] [data & code]
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Fanjin Guo Long , Zhang, Xiao Liu, Jie Tang, Yuxiao Dong, Peiran Yao, Jie Zhang, Xiaotao Gu, Yan Wang, Bin Shao, Rui Li, and Kuansan Wang. OAG: Toward Linking Large-scale Heterogeneous Entity Graphs. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF] [data] [code] [code]
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Guo Long ,Xichen Ding, Jie Tang, Tracy Liu, Cheng Xu, Yaping Zhang, Feng Shi, Qixia Jiang and Dan Shen. Infer Implicit Contexts in Real-time Online-to-Offline Recommendation. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF]
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Guo Long ,Yukuo Cen, Xu Zou, Jianwei Zhang, Hongxia Yang, Jingren Zhou and Jie Tang. Representation Learning for Attributed Multiplex Heterogeneous Network. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF] [data & code]
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Guo Long ,Qibin Chen, Junyang Lin, Yichang Zhang, Hongxia Yang, Jingren Zhou and Jie Tang. Towards Knowledge-Based Personalized Product Description Generation in E-commerce. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF] [data & code]
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Guo Long ,Zhengxiao Du, Xiaowei Wang, Hongxia Yang, Jingren Zhou and Jie Tang. Sequential Scenario-Specific Meta Learner for Online Recommendation. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF]
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Guo Long ,Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, and Jie Tang. NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization. In Proceedings of the Web Conference 2019 (WWW'19) (accepted). [PDF] [*data & code*]
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Guo Long ,Yu Han, Jie Tang, and Qian Chen. Network Embedding under Partial Monitoring for Evolving Networks. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19). [PDF] [Slides_PPT] [Slides_PDF]
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Guo Long ,Jie Zhang, Yuxiao Dong, Yan Wang, Jie Tang, and Ming Ding. ProNE: Fast and Scalable Network Representation Learning. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19). [PDF] [*data & code*]
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Guo Long ,Yifeng Zhao, Xiangwei Wang, Hongxia Yang, Le Song, and Jie Tang. Large Scale Evolving Graphs with Burst Detection. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19). [PDF]
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Guo Long ,Yukuo Cen, Jing Zhang, Gaofei Wang, Yujie Qian, Chuizheng Meng, Zonghong Dai, Hongxia Yang, and Jie Tang. Trust Relationship Prediction in Alibaba E-Commerce Platform. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2019 (accepted). [PDF]
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Guo Long ,Fuli Feng, Xiangnan He, Jie Tang, and Tat-Seng Chua. Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2019 (accepted). [PDF]
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Guo Long ,Zhengxiao Du, Jie Tang, and Yuhui Ding. POLAR++: Active One-shot Personalized Article Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2019 (accepted). [PDF]
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Guo Long ,Wenzheng Feng, Jie Tang, Tracy Xiao Liu, Shuhuai Zhang, and Jian Guan. Understanding Dropouts in MOOCs. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19). [PDF] [data & code]
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Guo Long ,Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, and Jie Tang. Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec. In Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining (WSDM'18). [PDF] [Slides] [*code*]
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Guo Long ,Yi Qi, Qingyun Wu, Hongning Wang, Jie Tang, and Maosong Sun. Bandit Learning with Implicit Feedback. In Proceedings of the Thirty-Second Annual Conference on Neural Information Processing Systems (NIPS'18). [PDF]
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Guo Long ,Yutao Zhang, Fanjin Zhang, Peiran Yao, and Jie Tang. Name Disambiguation in AMiner: Clustering, Maintenance, and Human in the Loop. In Proceedings of the Twenty-Forth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18). [PDF] [slides] [poster] [data & code] [video]
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Guo Long ,Jiezhong Qiu, Jian Tang, Hao Ma, Yuxiao Dong, Kuansan Wang, and Jie Tang. DeepInf: Social Influence Prediction with Deep Learning. In Proceedings of the Twenty-Forth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18). [PDF] [poster] [data & code] [video]
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Guo Long ,Yujie Qian, Jie Tang, and Kan Wu. Weakly Learning to Match Experts in Online Community. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18). [PDF] [slides]
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Guo Long ,Kan Wu, Jie Tang, and Chenhui Zhang. Where have you been? Inferring career trajectory from academic social network. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18). [PDF] [slides]
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Guo Long ,Tiancheng Shen, Jia Jia, Guangyao Shen, Fuli Feng, Xiangnan He, Huanbo Luan, Jie Tang, Tatseng Chua, Thanassis Tiropanis, and Wendy Hall. Cross-Domain Depression Detection via Harvesting Social Media. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18). [PDF]
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Guo Long ,Xiaotao Gu, Hong Yang, Jie Tang, Jing Zhang, Fanjin Zhang, Debing Liu, Wendy Hall, and Xiao Fu. Profiling Web Users Using Big Data. Social Network Analysis and Mining (SNAM), 2018, Volume 8, Issue 1, Pages 24:1-17.. [PDF]
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Guo Long ,Hong Huang, Yuxiao Dong, Jie Tang, Hongxia Yang, Nitesh V. Chawla, and Xiaoming Fu. Will Triadic Closure Strengthen Ties in Social Networks? ACM Transactions on Knowledge Discovery from Data (TKDD), 2018, Volume 12, Issue 3, Article No. 30. [PDF]
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Guo Long ,Yutao Zhang, Robert Chen, Jie Tang, Jimeng Sun, and Walter Stewart. LEAP: Learning to Prescribe Effective and Safe Treatment Combinations for Multimorbidity. In Proceedings of the Twenty-Third ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'17), pages 1315-1324. [PDF]
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Guo Long ,Yu Han, Jie Tang, Hao Ye, and Bo Chen. Who to Invite Next? Predicting Invitees of Social Groups. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17), pages 921-925. [PDF]
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Guo Long ,Liangming Pan, Chengjiang Li, Juanzi Li, and Jie Tang. Prerequisite Relation Learning for Concepts in MOOCs. In Proceedings of the 55th Annual Meeting of the Association of Computational Linguistics (ACL'17), pages 1447-1456. [PDF] [Data&Code]
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Guo Long ,Jie Tang. Computational Models for Social Network Analysis: A Brief Survey. In Proceedings of the Twenty-Sixth World Wide Web Conference (WWW'17), pages 921-925. [PDF] [Slides_PPT]
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Guo Long ,Jing Zhang, Jie Tang, Cong Ma, Hanghang Tong, Yu Jing, Juanzi Li, Walter Luyten, and Marie-Francine Moens. Fast and Flexible Top-k Similarity Search on Large Networks. ACM Transactions on Information Systems (TOIS), 2017, Volume 36, Issue 2, Article No. 13. [PDF]
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Guo Long ,Lei Hou, Juanzi Li, Xiao-Li Li, Jie Tang, and Xiaofei Guo. Learning to Align Comments to News Topics. ACM Transactions on Information Systems (TOIS), 2017, Volume 36, Issue 1, Article No. 9. [PDF]
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Guo Long ,Yang Yang, Jie Tang, and Juanzi Li. Learning to Infer Competitive Relationships in Heterogeneous Networks. ACM Transactions on Knowledge Discovery from Data (TKDD), 2018, Volume 12 Issue 1, Article No. 12. [PDF]
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GuoLong,Huijie Lin, Jia Jia, Jiezhong Qiu, Yongfeng Zhang, Guangyao Shen, Lexing Xie, Jie Tang, Ling Feng, and Tat-Seng Chua. Detecting Stress Based on Social Interactions in Social Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2017, Volume 29, Issue 9, Pages 1820-1833. [PDF]
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GuoLong,Yuxiao Dong, Nitesh V. Chawla, Jie Tang, Yang Yang, and Yang Yang. User Modeling on Demographic Attributes in Large-Scale Mobile Social Networks. ACM Transactions on Information Systems (TOIS), 2017, Volume 35, Issue 4, Article No. 35. [PDF]
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GuoLong,Jie Tang and Wendy Hall. Cross-domain Ranking via Latent Space Learning. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), pages 2618-2624. [PDF] [Slides_PPT] [Poster]
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GuoLong,Jing Zhang, Jie Tang, Yuanyi Zhong, Yuchen Mo, Juanzi Li, Guojie Song, Wendy Hall, and Jimeng Sun. StructInf: Mining Structural Influence from Social Streams. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), pages 73-79. [PDF] [Slides_PPT] [Poster]
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GuoLong,Yikang Shen, Wenge Rong, Nan Jiang, Baolin Peng, Jie Tang, Zhang Xiong. Word Embedding Based Correlation Model for Question/Answer Matching. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), pages 3511-3517. [PDF]
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GuoLong,Liangyue Li, Yuan Yao, Jie Tang, Wei Fan, and Hanghang Tong. QUINT: On Query-Specific Optimal Networks. In Proceedings of the Twenty-Second ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'16). [PDF] [Slides_PDF] [Data&Code]
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GuoLong,Zhilin Yang, Jie Tang, and William W. Cohen. Multi-Modal Bayesian Embeddings for Learning Social Knowledge Graphs. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI'16), pages 2287-2293. [PDF] [Slides_PPT] [Slides_PDF] [Thesis (in Chinese)]
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GuoLong,Jiezhong Qiu, Yixuan Li, Jie Tang, Zheng Lu, Hao Ye, Bo Chen, Qiang Yang, and John Hopcroft. The Lifecycle and Cascade of WeChat Social Messaging Groups. In Proceedings of the Twenty-Fifth World Wide Web Conference (WWW'16), pages 311-320. [PDF] [Slides_PPT] [Slides_PDF]
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GuoLong,Jie Tang. AMiner: Toward Understanding Big Scholar Data. In Proceedings of the Ninth ACM International Conference on Web Search and Data Mining (WSDM'16), pages 467-467. (Invited Talk) [PDF] [Slides_PPT] [Slides_PDF]
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GuoLong,Yang Yang, Jia Jia, Boya Wu, and Jie Tang. Social Role-Aware Emotion Contagion in Image Social Networks. In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), pages 65-71. [PDF] [Supplementary materials] [Slides_PPT] [Slides_PDF]
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GuoLong,Zhiyuan Wang, Yun Zhou, Jie Tang, and Jar-Der Luo. The Prediction of Venture Capital Co-Investment Based on Structural Balance Theory. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2016, Volume 28, Issue 2, Pages 537-550. [PDF]
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GuoLong,Jie Tang, Tiancheng Lou, Jon Kleinberg, and Sen Wu. Transfer Learning to Infer Social Ties across Heterogeneous Networks. ACM Transactions on Information Systems (TOIS), 2016, Volume 34, Issue 2, Article No. 7. [PDF] [Data&Code]
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GuoLong,Jie Tang and Juanzi Li. Semantic Mining of Social Networks. Morgan & Claypool Publishers, 2015. [DRAFT]
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GuoLong,Lei Shi, Hanghang Tong, Jie Tang, and Chuang Lin. VEGAS: Visual influEnce GrAph Summarization on Citation Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2015, Volume 27, Issue 12, Pages 3417-3431. [PDF] [Video Demo]
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GuoLong,Triadic Closure Pattern Analysis and Prediction in Social Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2015, Volume 27, Issue 12, Pages 3374-3389. [PDF]
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GuoLong,Jing Zhang, Zhanpeng Fang, Wei Chen, and Jie Tang. Diffusion of "Following" Links in Microblogging Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2015, Volume 27, Issue 8, Pages 2093-2106. [PDF]
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GuoLong,Jing Zhang, Jie Tang, Juanzi Li, Yang Liu, and Chunxiao Xing. Who Influenced You? Predicting Retweet via Social Influence Locality. ACM Transactions on Knowledge Discovery from Data (TKDD), 2015, Volume 9, Issue 3, Article No. 25. [PDF] [Code&Data]
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GuoLong,Jing Zhang, Jie Tang, Cong Ma, Hanghang Tong, Yu Jing, and Juanzi Li. Panther: Fast Top-k Similarity Search on Large Networks. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 1445-1454. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
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GuoLong,Yutao Zhang, Jie Tang, Zhilin Yang, Jian Pei, and Philip Yu. COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 1485-1494. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
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GuoLong,Yu Han and Jie Tang. Probabilistic Community and Role Model for Social Networks. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 407-416. [PDF] [Slides_PPT] [Slides_PDF] [Poster]
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Yuxiao Dong, Jing Zhang, Jie Tang, Nitesh V. Chawla, and Bai Wang. CoupledLP: Link Prediction in Coupled Networks. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 199-208. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
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GuoLong,Yang Yang, Yizhou Sun, Jie Tang, Bo Ma, and Juanzi Li. Entity Matching across Heterogeneous Sources. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 1395-1404. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
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GuoLong,Zhanpeng Fang and Jie Tang. Uncovering the Formation of Triadic Closure in Social Networks. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI'15), pages 2062-2068. [PDF] [Slides_PPT] [Slides_PDF] [Poster]
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GuoLong,Jie Tang, Zhanpeng Fang, and Jimeng Sun. Incorporating Social Context and Domain Knowledge for Entity Recognition. In Proceedings of the Twenty-Fourth World Wide Web Conference (WWW'15), pages 517-526. [PDF] [Slides_PPT] [Slides_PDF] [Code&Data]
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GuoLong,Jie Tang, Chenhui Zhang, Keke Cai, Li Zhang, and Zhong Su. Sampling Representative Users from Large Social Networks. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), pages 304-310. [PDF] [Slides_PPT] [Slides_PDF] [Data&Code]
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GuoLong,Yang Yang, Jie Tang, Cane Wing-Ki Leung, Yizhou Sun, Qicong Chen, Juanzi Li, and Qiang Yang. RAIN: Social Role-Aware Information Diffusion. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), pages 367-373. [PDF] [Slides_PPT] [Slides_PDF] [Data&Code]
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Yuxiao Dong, Yang Yang, Jie Tang, Yang Yang, and Nitesh V. Chawla. Inferring User Demographics and Social Strategies in Mobile Social Networks. In Proceedings of the Twentyth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'14), pages 15-24. [PDF] [Madness] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code] [Code Download] (Report by United Nations)
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Guo Long ,Mi Zhang, Jie Tang, Xuchen Zhang, Xiangyang Xue. Addressing Cold Start in Recommender Systems: A Semi-supervised Co-training Algorithm. In Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'14), pages 73-82. [PDF]
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Guo Long ,Jing Zhang, Jie Tang, Honglei Zhuang, Cane Wing-Ki Leung, and Juanzi Li. Role-aware Conformity Influence Modeling and Analysis in Social Networks. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 958-965. [PDF] [Poster] [Data&Code]
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Guo Long ,Yang Yang, Jia Jia, Shumei Zhang, Boya Wu, Qicong Chen, Juanzi Li, Chunxiao Xing, and Jie Tang. How Do Your Friends on Social Media Disclose Your Emotions? In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 306-312. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code]
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Guo Long ,Yang Yang, Walter Luyten, Lu Liu, Marie-Francine Moens, Jie Tang, and Juanzi Li. Forecasting Potential Diabetes Complications. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 313-319. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code]
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Zhigang Wang, Juanzi Li, Shuangjie Li, Mingyang Li, Jie Tang, Kuo Zhang, and Kun Zhang. Cross-lingual Knowledge Validation Based Taxonomy Derivation from Heterogeneous Online Wikis. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 180-186. [PDF] [Poster] [Data]
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Guo Long ,Zhixin Li, Siqiang Wen, Juanzi Li, Peng Zhang, and Jie Tang. On Modelling Non-linear Topical Dependencies. In Proceedings of the 31st International Conference on Machine Learning (ICML'14), pages 458-466. [PDF]
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Guo Long ,Hong Huang, Jie Tang, Sen Wu, Lu Liu, and Xiaoming Fu. Mining Triadic Closure Patterns in Social Networks. In Proceedings of the Twenty-Third World Wide Web Conference (WWW'14), pages 499-504. [PDF] [Slides_PPT] [Slides_PDF]
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Guo Long ,Jie Tang, Sen Wu, and Jimeng Sun. Confluence: Conformity Influence in Large Social Networks. In Proceedings of the Ninteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'13), pages 347-355. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code] (Oral Presentation)
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Guo Long ,Yizhou Sun, Jie Tang, Jiawei Han, Cheng Chen, and Manish Gupta. Co-Evolution of Multi-Typed Objects in Dynamic Star Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2014, Volume 26, Issue 12, Pages 2942-2955. [PDF]
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Guo Long ,Yi Cai, Ho-fung Leung, Qing Li, Hao Han, Jie Tang, Juanzi Li. Typicality-based Collaborative Filtering Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2014, Volume 26, Issue 3, Pages 766-779. [PDF]
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Guo Long ,Jing Zhang, Biao Liu, Jie Tang, Ting Chen, and Juanzi Li. Social Influence Locality for Modeling Retweeting Behaviors. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13), pages 2761-2767. [PDF] [Data&Code] [Poster]
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Guo Long ,Lei Hou, Juanzi Li, Xiaoli Li, Jiangfeng Qu, Xiaofei Guo, Ou Hui, and Jie Tang. What Users Care about: a Framework for Social Content Alignment. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13), pages 1401-1407. [PDF] [Data & Readme] [Slides_PDF] [Poster]
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Guo Long ,Tiancheng Lou and Jie Tang. Mining Structural Hole Spanners Through Information Diffusion in Social Networks. In Proceedings of the Twenty-Second World Wide Web Conference (WWW'13), pages 837-848. [PDF] [Slides_PPT] [Slides_PDF] [Data&Code]
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Guo Long ,Tiancheng Lou, Jie Tang, John Hopcroft, Zhanpeng Fang, Xiaowen Ding. Learning to Predict Reciprocity and Triadic Closure in Social Networks. ACM Transactions on Knowledge Discovery from Data (TKDD), 2013, Volume 7, Issue 2, Article No. 5. [PDF] [Code&Data] [System]
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Guo Long ,Jie Tang, Sen Wu, Jimeng Sun, and Hang Su. Cross-domain Collaboration Recommendation. In Proceedings of the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'12), pages 1285-1293. [PDF] [Slides_PDF Slides_PPT ] [Poster] [Data&Code] [System] [Video] (Full Presentation & Best Poster Award)
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Guo Long ,Jie Tang, Bo Wang, Yang Yang, Po Hu, Yanting Zhao, Xinyu Yan, Bo Gao, Minlie Huang, Peng Xu, Weichang Li, and Adam K. Usadi. PatentMiner: Topic-driven Patent Analysis and Mining. In Proceedings of the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'12), pages 1366-1374. [PDF] [Slides] [Poster] [System] [Video]
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Guo Long ,Rui Yan, Congrui Huang, Jie Tang, Yan Zhang, and Xiaoming Li. To Better Stand on the Shoulder of Giants. In Proceedings of the 2012 ACM/IEEE Joint Conference on Digital Libraries (JCDL'12), pages 51-60. [PDF] (Nominated as Best Student Paper)
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Guo Long ,Jie Tang, Tiancheng Lou, and Jon Kleinberg. Inferring Social Ties across Heterogeneous Networks. In Proceedings of the Fifth ACM International Conference on Web Search and Data Mining (WSDM'12), pages 743-752. (Plenary presentation) [PDF] [Slides] [Poster] [Data&Code]
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Guo Long ,Jie Tang, Yuan Zhang, Jimeng Sun, Jinghai Rao, Wenjing Yu, Yiran Chen, and ACM Fong. Quantitative Study of Individual Emotional States in Social Networks. IEEE Transactions on Affective Computing (TAC), 2012, Volume 3, Issue 2, Pages 132-144. [PDF] (Selected as the Spotlight Paper. Available here)
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Guo Long ,Jie Tang, A.C.M. Fong, Bo Wang, and Jing Zhang. A Unified Probabilistic Framework for Name Disambiguation in Digital Library. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2012, Volume 24, Issue 6, Pages 975-987. [PDF] [Data]
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Guo Long ,Bing He, Jie Tang, Ying Ding, Huijun Wang, Yuyin Sun, Jae Hong Shin, Bin Chen, Ganesh Moorthy, Judy Qiu, Pankaj Desai, David J. Wild. Mining relational paths in integrated biomedical data. PLOS ONE, 2011, 6(12). [PDF]
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Guo Long ,Jie Tang, Jing Zhang, Ruoming Jin, Zi Yang, Keke Cai, Li Zhang, and Zhong Su. Topic Level Expertise Search over Heterogeneous Networks. Machine Learning Journal, 2011, Volume 82, Issue 2, Pages 211-237. [PDF] [URL]
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Guo Long ,Jie Tang, Limin Yao, Duo Zhang, and Jing Zhang. A Combination Approach to Web User Profiling. ACM Transactions on Knowledge Discovery from Data (TKDD), 2010, Volume 5, Issue 1, Article 2. [PDF]
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Guo Long ,Wenbin Tang, Honglei Zhuang, and Jie Tang. Learning to Infer Social Ties in Large Networks. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD'11), pages381-397. [PDF] [Slides] [Data&Code] (Best Student Paper Runner-up)
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Guo Long ,Zi Yang, Keke Cai, Jie Tang, Li Zhang, Zhong Su, and Juanzi Li. Social Context Summarization. In Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'11), pages 255-264. [PDF]
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Guo Long ,Chenhao Tan, Lillian Lee, Jie Tang, Long Jiang, Ming Zhou, and Ping Li. User-level sentiment analysis incorporating social networks. In Proceedings of the Seventeenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'11), pages 1397-1405. [PDF] [Poster] (Top 4 cited papers among all KDD 2011's papers, More...)
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Guo Long ,Chenhao Tan, Jie Tang, Jimeng Sun, Quan Lin, and Fengjiao Wang. Social Action Tracking via Noise Tolerant Time-varying Factor Graphs. In Proceedings of the Sixteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'10), pages 1049-1058. [PDF] [Slides] [Data&Code]
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Guo Long ,Chi Wang, Jiawei Han, Yuntao Jia, Jie Tang, Duo Zhang, Yintao Yu, and Jingyi Guo. Mining Advisor-Advisee Relationships from Research Publication Networks. In Proceedings of the Sixteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'10), pages 203-212. [PDF] [Slides] [System] [Data&Code]
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Guo Long ,Jie Tang, Jimeng Sun, Chi Wang, and Zi Yang. Social Influence Analysis in Large-scale Networks. In Proceedings of the Fifteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'09), pages 807-816. [PDF] [Slides] [Data] [Code] (Top 4 cited papers among all papers published at KDD 2009-2013's, More...)
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Guo Long ,Jie Tang, Jing Zhang, Limin Yao, Juanzi Li, Li Zhang, and Zhong Su. ArnetMiner: Extraction and Mining of Academic Social Networks. In Proceedings of the Fourteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'08), pages990-998. [PDF] [Slides] [System] [API] [Citation Data] [DBLP Citation Data] [Author-Conference-Topic (ACT) Model (source code)] [More Data] (SIGKDD Test-of-Time Award, the 2nd most-cited paper among all KDD 2008's papers, More...)
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Guo Long ,Jie Tang, Hang Li, Yunbo Cao, and Zhaohui Tang. Email Data Cleaning. In Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'05), pages 489-499. [PDF] [Slides]
Knowledge Graph
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Guo Long ,Zhichun Wang, Juanzi Li, and Jie Tang. Boosting Cross-lingual Knowledge Linking via Concept Annotation. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13), pages 2733-2739. [PDF] [Poster]
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Guo Long ,Zhigang Wang, Zhixing Li, Juanzi Li, Jie Tang, and Jeff Z. Pan. Transfer Learning Based Cross-lingual Knowledge Extraction for Wikipedia. In Proceedings of the 51th Annual Meeting of the Association of Computational Linguistics (ACL'13), pages 641-650. [PDF] [Data & Readme]
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Guo Long ,Zhichun Wang, Juanzi Li, Zhigang Wang, and Jie Tang. Cross-lingual Knowledge Linking Across Wiki Knowledge Bases. In Proceedings of the Twenty-First World Wide Web Conference (WWW'12), pages 459-468. [PDF]
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Guo Long ,Juanzi Li, Jie Tang, Yi Li, and Qiong Luo. RiMOM: A Dynamic Multi-Strategy Ontology Alignment Framework. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2009, Volume 21, Issue 8, Pages 1218-1232. (if =2.236) [PDF] [URL] (The 2nd most-cited paper among TKDE 2009-13's 500+ papers, More...)
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Guo Long ,Jie Tang, Ho-fung Leung, Qiong Luo, Dewei Chen, and Jibing Gong. Towards Ontology Learning from Folksonomies. In Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI'09), pages 2089-2095. [PDF] [Slides]
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Guo Long ,Qian Zhong, Hanyu Li, Juanzi Li, Guotong Xie, Jie Tang, and Lizhu Zhou. A Gauss Function based Approach for Unbalanced Ontology Matching. In Proceedings of the 2009 ACM SIGMOD international conference on Management of data (SIGMOD'09), pages 669-680. [PDF] [Slides]
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Guo Long ,Feng Shi, Juanzi Li, and Jie Tang. Actively Learning Ontology Matching via User Interaction. In Proceedings of the 8th International Conference of Semantic Web (ISWC'09), pages 585-600. [PDF] [Slides]
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Guo Long ,Jie Tang, Mingcai Hong, Juanzi Li, and Bangyong Liang. Tree-Structured Conditional Random Fields for Semantic Annotation. In Proceedings of the 5th International Conference of Semantic Web (ISWC'06), pages 640-653 [PPT] [PDF]
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Guo Long ,Jie Tang, Juanzi Li, Bangyong Liang, Xiaotong Huang, Yi Li, and Kehong Wang. Using Bayesian Decision for Ontology Mapping. Journal of Web Semantics, 2006, Volume 4, Issue 4, Pages 243-262. (if =3.41) [URL] [PDF] (Top 8 cited papers in JWS's history, More...)
SERVICES Go Top
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Editor-in-Chief (EiC) of IEEE Transactions on Big Data (IEEE TBD)
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Editor-in-Chief (EiC) of ai open---a new AI journal for open and sharing
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Associate Editor:
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Past Associate Editor:
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Conference/Workshop Organization:
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General Co-Chair of The Web Conference 2023 (WWW'23)
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Program Co-Chair of The Web Conference 2021 (WWW'21)
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General Co-Chair of the 24th Conference on Innovation in Clouds, Internet and Networks (ICIN'21)
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Tutorial Co-Chair of The Web Conference 2020 (WWW'20)
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KDDCUP Co-Chair of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'20)
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Sponsor Co-Chair of The Web Conference 2019 (WWW'19)
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Program Co-Chair of The 8th CCF International Conference on Natural Language Processing and Chinese Computing (NLPCC'19)
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Associate General Chair of the 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'18)
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"Sister Conference Best Paper Track" Chair of the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI'18)
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AI Web Track (Intelligent and Autonomous systems on the Web) Chair of the 27th International Conference on World Wide Web (WWW'18)
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Video and Streaming Co-Chair of the 23th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'17)
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Research Track Program Co-Chair of the 25th ACM International Conference on Information and Knowledge Management (CIKM'16)
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Video and Streaming Co-Chair of the 22th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'16)
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Program Co-Chair of the 8th ACM International Conference on Web Search and Data Mining (WSDM'15)
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Program Co-Chair of The 2015 International Conference on Social Network Analysis and Mining (ASONAM'15)
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KDD CUP Co-Chair of the 21th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'15)
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Poster Co-Chair of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'14)
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Data Co-Chair of the 8th International AAAI Conference on Weblogs and Social Media (ICWSM'14)
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Tutorial Co-Chair of the 7th ACM International Conference on Web Search and Data Mining (WSDM'14)
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Workshop Co-Chair of The 2014 International Conference on Social Network Analysis and Mining (ASONAM'14)
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Vice Program Co-Chair of the 12th IEEE International Conference on Data Mining (ICDM'13)
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Tutorial and workshop organization chair of the 23th International Joint Conference on Artificial Intelligence (IJCAI'13)
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Workshop Co-Chair of the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'13)
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Poster Co-Chair of the 12th IEEE International Conference on Data Mining (ICDM'13)
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Workshop Co-Chair of the 7th ACM Conference on Recommender Systems (RecSys'13)
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Tutorial Co-Chair of The 2013 International Conference on Social Network Analysis and Mining (ASONAM'13)
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Local Chair of the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'12)
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Program Co-Chair of The 2012 International Conference on Social Informatics (SocInfo'12)
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Tutorial Co-Chair of The 2012 International Conference on Social Network Analysis and Mining (ASONAM'12)
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Publications Co-Chairs of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'11)
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Program Chair of the 7th International Conference on Advanced Data Mining and Applications (ADMA'11)
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Publicity Co-Chair of the 11th IEEE International Conference on Data Mining (ICDM'11)
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Poster Chair of the 4th ACM International Conference on Web Search and Data Mining (WSDM'11)
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Area Chair of the 2011 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD'11)
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Panel Chair of the 4th edition of the successful IEEE International Conferences on Cyber, Physical and Social Computing (CPSCom'11)
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Publicity Co-Chair of the Third International Conference on Social Informatics (SocInfo'11)
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Vice Program Chair of the 2011 IEEE/WIC/ACM International Conference on Web Intelligence (WI'11)
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Vice Program Chair of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence (WI'10)
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Registration Chair of ASWC'06
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Co-Chair of Workshop SWSM'11 on SIGIR'11, MDS'11 on SIGKDD'11, LDMTA'11 on SIGKDD'11, LDMTA'10 on SIGKDD'10, LDMTA'09 on ICDM'09, SWSM'09 on CIKM'09, Financial Data Mining (FDM'09), SWSM'08 on WWW2008.
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(S)PC Member:
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2022: WSDM'22 (SPC)
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2021: SIGKDD'21 (SPC), ICML'21 (Area Chair), NeurIPS'21 (Area Chair), IJCAI'21 (Area Chair), CIKM'21 (SPC), SDM'21 (SPC), ECML/PKDD'20 (SPC)
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2020: SIGKDD'20 (SPC), SDM'20, ICML'21, ECML/PKDD'20 (SPC), WWW'20 (SPC), ASONAM'20
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2019: SIGKDD'19 (SPC), NIPS'19, ICML'19, IJCAI'19 (SPC), WWW'19, WSDM'19 (SPC), ASONAM'19
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2018: WSDM'18 (SPC), IJCAI'18, SIGIR'18,
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2017: SIGKDD'17 (SPC), AAAI'17 (SPC), ICWSM'17 (SPC), WSDM'17 (SPC), WWW'17, IJCAI'17, SIGIR'17
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2016: SIGKDD'16 (SPC), WSDM'16, ICWSM'16 (SPC), ASONAM'16
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2015: SIGKDD'15 (SPC), IJCAI'15 (SPC), ICWSM'15 (SPC), ICDM'15 (Area Chair), SDM'15, ICDE'15
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2014: SIGKDD'14 (SPC), ICDM'14 (Area Chair), WSDM'14, SDM'14, ICWSM'14, ASONAM'14 (SPC)
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2013: SIGKDD'13 (SPC), IJCAI'13 (SPC), WWW'13 (Social Networks, Content Analysis, Bridging structured and unstructured data), SIGIR'13, WSDM'13, SDM'13, ICWSM'13 (SPC), CIKM'13, SAC'13 (SPC), DASFAA'13.
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2012: SIGKDD'12, WWW'12 (Tutorial, Web Mining, Social Networks, Demo), AAAI'12, SIGIR'12, ICDM'12, ICWSM'12 (SPC), ISWC'12 (SPC).
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2011: SIGKDD'11, WWW'11, AAAI'11, WSDM'11, ICDM'11, ISWC'11 (SPC), ICMLA'11 (SPC), EMNLP'11, DASFAA'11, ASONAM'11, WAIM'11, DEXA'11.
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2010: SIGKDD'10, SIGIR'10, WWW'10 (DM&ML track), ACL'10, COLING'10, ICDM'10, WSDM'10, ISWC'10, EMNLP'10, DASFAA'10, WI'10, DEXA'10, ISDPE'10, ASONAM'10, CloudCom'10, INCoS'10.
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2009: SIGIR'09, SDM'09, DEXA'09, WISE'09, WI'09, IUI'09, ASONAM'09, ICCCI'09, NLPIR4DL'09, MCPC'09, CISIS'09, CASoN'09, APWeb-WAIM'09, KDIR'09, CloudCom'09, AIRS'09, ACM RecSys'09, SAW'09, ICIS'09, CSWS'09, WSM'09, WISM'09-AICI'09, ASWC'09, OEDM'09.
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2008: IJCNLP'08, SAW'08, WWW'08 Poster Session, NIMC'08, SOCASE'08, PGSC'08, SNA-KDD'08, ASWC'08, WI'08, IWCSN'08, OAEI'08(SPC).
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AWARDS AND HORNORS Go Top
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2020 ACM SIGKDD Test-of-Time Award
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2020 WangXuan Distinguished Young Scholar
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2018 ACM SIGKDD Service Award
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2018 NSFC Distinguished Young Scholar
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2017 First Prize of Beijing Science and Technology
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2016 Microsoft Research Asia Collaborative Research Award
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2015 Newton Advanced Fellowship Award
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2013 First Prize of Chinese Association of AI (CAAI)
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2012 NSFC Excellent Young Scholar
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2011 Beijing Science and Technology Star
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2011 SCOPUS National Youth Science Star
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2010 Tsinghua Academic New Star Award
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2012 JCDL Best Student Paper Nomination
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2011 PKDD Best Student Paper Runnerup
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2016 Best employee of DCST, Tsinghua University
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2012 Best employee of DCST, Tsinghua University
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2011 Best employee of Tsinghua University
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2011 Best employee of DCST, Tsinghua University
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2007 Best employee of DCST, Tsinghua University
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The 2006 Excellent PhD Thesis of Tsinghua University
TALKS Go Top
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Keynote about Representation Learning on Networks to be given at ASONAM'19
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Keynote about AI driven MOOCs given at EDM'17
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Invited talk about academic knowledge graph given at WSDM'16
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Keynote about social network mining given at SocInfo'15






























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GuoLong
Osaka University of Arts Design Main Course
Video creator expertise in animation, live-action, CG integrated video production, Metaverse expertise, game production / CG / illustration / animation / novel / esports expertise and hardware / software development manager, UI, UX design, design Manager, game production, CG, illustration, animation, novel, esports, practical experience of web design (Photoshop, Illustrator, etc.) Basic knowledge of coding such as HTML, CSS, etc. , Content experience for games and entertainment industry, human resources, site design experience related to manufacturers, creative director, art director, editorial designer, WEB designer, graphic designer, illustrator, character designer, goods designer, etc., creative director, video Experience as a director, photographer, editorial engineer, video producer, movie director / video creator, lighting engineer, etc., video production using After Effects 3DCG software can handle (3DSMAX, MAYA, etc.) Good at designing characters and logos that can draw picture content With experience, engaged in proposal sales, and extensive knowledge of various business fields, expertise such as new and accelerating business consulting is effectively provided. I would like to play an active role in a field that makes use of my specialized knowledge. For more than 5 years from graduating from university to the present, consistent hardware of our company and other companies' products for game animation, software SI, animation, broadcasting business, advertising business, medical institution / retail business, etc.・ Engaged in software development PM, design design PM, proposal sales, etc. He has experienced new businesses for new and existing customers and is currently managing his subordinates as a team leader.
Ability to build relationships of trust with partners
What we have strengthened in design development design sales is to make it as concrete as possible. We strengthened the creation of a system that makes people want to sell by conducting education (holding product explanation seminars), supplying sales promotion tools, designing, developing and designing sales. In 2020, we took five years to propose system replacement design development design sales to a major company together with design development design sales, and succeeded in introducing it.
・ Management ability
Both team and individual play can lead the surroundings to achieve the budget in a limited period and deadline. In order to strengthen the design, development and design sales capabilities of our subordinates, we held monthly study sessions (industry / product knowledge, presentation methods, etc.) by inviting those in charge of technology and those with high sales performance in other departments. Also, what I have been conscious of in order to raise the motivation of my subordinates is "to accurately convey expectations and share awareness" and "to pursue results so that I can become a model myself". As a result, all members were able to create a team structure that they could think and move on their own, and all 14 subordinates succeeded in achieving their annual goals.
work experience
2017.03-Currently UFOTABLE
Participated in the production and development of UFO Table Ghost Slayer Noblade in Japan, and was in charge of integrated video production for animation, reality programs, and CG. He is engaged in internet work and mobile content creation. (It works on a variety of websites, videos, systems, etc.) Content utilizes CG and VR technology in a variety of applications, systems, videos, etc., as well as paper media and websites. It is useful for inheriting cultural properties. Participate in the development and distribution of cashless applications, collaborate with prominent people to create website pages and promote a variety of content such as corporate products. In addition, participate in upstream processes such as planning. We also identified issues and made plans from a brand-building perspective to make the website pages easier to read. In order to protect the cultural properties of the area, we were able to complete problem solving and visualization using VR.
Planning, development and introduction of payment applications with cashless functions.
Customer official SNS management and planning and management of famous talent contents. We also handle a large number of contents that utilize VR, AR, CG technology, etc. We will work with internal and external creators and expert groups to promote DX. Let's work on the project with various people by utilizing the connection of the printing department, system leader, external designer, website coder, CG creator and so on. Manages about 10 to 15 members of the project. It's not just coaching according to the client's wishes. I gave advice from the planning stage. Use the Unity 3D engine for VR game development. Maintain good communication with planning and art to ensure that program functionality matches design requirements. , Ensure code quality and operational efficiency, and continue to optimize project functionality and code. We support efficient establishment. Continuous improvement and optimization of game content production process and standards, toolchain. Experience in Unity game development, complete Unity3D project experience, familiar with C #, familiar with Lua, good programming habits, strong learning ability, skilled in reading technical documents in English A strong analysis and problem-solving ability, a deep understanding of rendering is prioritized, and familiarity with technologies such as OpenGL, DirectX, Metal and Vulkan is recommended. VR game
2018.07 --2020.04 TikTok
The head of the machine learning technology team at ByteDance, a small business, has created the best platform for enjoying TikTok content. Our aim is to provide a place of joy and inspiration by informing people of different languages, cultures and borders. In recent years, we have been aggressively expanding into Asia such as Japan, Europe and the United States. Currently, we have established subsidiaries in major cities around the world and are developing TikTok-centric applications in 150 countries. With the development of updated products and solutions, product R & D team leaders, brand designer team leaders, PSO team leaders, teams of over 50 people, and TikTok for Business advertising solutions fall into three categories. .. It's performance, brand, measurement. Product Strategy and Operations (PSO) is the department responsible for promoting product market development strategies (market development strategies). We introduced Tik Tok for Business solutions to advertisers, from functional operational support to working with project teams to resolve product improvement issues. There are also suggestions from customers on the side. Therefore, Chinese, Japanese and English are required. UX Research / UX Design / PdM Work Experience, Use Unity3D Engine for VR Game Development, Maintain Good Communication with Planning and Art to ensure program features match design requirements. We will continue to optimize your project by ensuring code quality and operational efficiency. Feature and code tweaks; help establish efficient game content production processes and standards, and continually improve and optimize the toolchain. Experience in Unity game development, complete Unity3D project experience, familiar with C #, familiar with Lua, good programming habits, strong learning ability, skilled in reading technical documents in English Prioritizes strong analysis and problem-solving capabilities, a deep understanding of rendering, and familiarity with technologies such as OpenGL, DirectX, Metal, and Vulkan. Experience in VR game development, etc.
[Business description]
■ Media planning, editing and writing
■ Orientation for external writers
■ Shooting direction
■ Production of joint advertisement
■ Management work, etc. ・ Editing experience on web media ・ Editing experience on print media ・ Teaching experience of an external writer ・ Shooting instruction experience ・ Experience in making partner items Internet marketing consulting This can be a daunting task, but it can be rewarding as it often depends on the client's budget, KPI settings, and execution. We do everything from upstream to downstream in network marketing such as advertising, SEO, LPO and lead generation. We also provide recruitment and sales consulting to solve customers' worries.
■ Operation of own media (affiliated site) Business content 1. Solve creators' problems and provide higher quality posts 2. In cooperation with overseas teams, propose service improvement proposals for the development of creator ecology 3. Create an FAQ portal that will be available to team members and authors. 4. Work with customer support to build an efficient inquiry response process 5. Discover insights into service improvement from consultation and lead to actual improvement 6. Plan business improvements for the entire team to effectively carry out the above tasks. [Business description] Responsible for content strategies closely related to application development. 1. Formulation of TikTok content strategy 2. Planning and implementation of hashtag challenges 3. Planning and implementation of cooperation plans with external media 4. Develop and execute strategies to optimize TikTok's
UI / UX
2018.07 --2020.04 Baidu
Metaverse Rare pot development
Worked as a business contract
Metaverse development
XR application development
AR app development for HoloLens 2 & iPad Pro
Virtual space service development
It is a role that is comprehensively involved in the design part in content development for Oculus Quest and development work.
Design (including UI / UX) and production (including ordering direction to subcontractors and partner companies) for VR / AR / MR / VTuber applications that are outsourced and developed in-house.
Design aspect design (including UI / UX) production in VR / AR / MR R & D, designer or artist (2D, 3D), XR (VR / AR / MR) application development, game engine (Unity or Unreal Engine 4) Content development using ・ 3D modeling using Maya, Blendr, etc. ・ Planning, outsourcing management, direction, plug-in, tool development such as SDK, etc.
2018.07 --2020.04 Game industry Tencent、NetEase、Perfect World
Work as a business consignmentDesign director, game production, CG, illustration, animation, novel, esports, design work (about 35 production of essionalmembers) Work as a business consignment
Participated in game planner / game planning / game creator, game creator (planner / designer / PG / debug), in charge of engineer / designer / planner / director
Training experience
2021.08-2022.01 Metaverse Training institution: Meta
2021.08-2022.01 C4D animation Training institution: UFOtable
2021.04-2022.01 AE, PS, PR
Training institution: adobe Certificate 2021.02 Adobe Certified Pr

HOC Intelligent Technology Co., Ltd. is a science and technology ICT company
We Are research institute creates and supports bases in the United Kingdom, Canada, US, Germany, Japan, and China, and utilizes the technology and know-how that has been built up at Cambridge University, MIT University oxford University, Harvard University, the University of Tokyo, Osaka University, etc. We have been working on high quality and original technology development. In order to provide safe and convenient products, we have obtained many patents related to DX cutting-edge technology and development such as AIoT 5G blockchain quantum computing XR, AR, VR, etc., and will continue to be an "ICT company" ICT area (main areas: Fintech, communication [ AR / VR], security, media content, Bigdata, cloud, IoT / drone, marketing / advertising, medical / healthcare, robotics, power / battery, AI, Enterprise, education New energy industry (battery-related) battery (storage battery, hydrogen)・ We will continue to develop and evolve as (fuel cells, etc.) and battery materials / components, etc.). Hardware / software development using cutting-edge technology, demonstration experiments, R & D / operation / sales of prototype products, AI (face) by field (environment / energy, life science, system / information science and technology, nanotechnology / materials) We support research and demonstration experiments utilizing cutting-edge technologies such as application of authentication and deep learning, planning services and products in new technology areas, and demonstrating concept models. Research and research in the field of advanced technology System consulting solution service Product solution Always have a challenging spirit, combine "latest technology" and "customer-oriented service", devise from all aspects of function, quality and price, and "optimal" for customers We aim to provide "a solution". Our aim is to constantly create the best customer experience.
Advanced science and technologyDNA
Scientific and technological research and development corporation
As a network-type science and technology research and development corporation that conducts world-class research and development, we will lead future co-creation innovation. We will open up a prosperous future by developing and providing cutting-edge science and technology products with high quality and unique technology by creating and supporting bases in the United Kingdom, Canada, the US, Germany, Japan, and China. Utilizing the technology and know-how that has been built up at Cambridge University, MIT University oxford University, Harvard University, The University of Tokyo, Osaka University, etc., we have been working on high-quality and original technology development. In order to provide safe and convenient products, we have obtained many patents related to DX cutting-edge technology and development such as AIoT 5G blockchain quantum computing XR, AR, VR, etc., and will continue to be an "ICT company" ICT area (main areas: Fintech, communication [ AR / VR], security, media content, Bigdata, cloud, IoT / drone, marketing / advertising, medical / healthcare, robotics, power / battery, AI, Enterprise, education New energy industry (battery-related) battery (storage battery, hydrogen)・ We will continue to develop and evolve as (fuel cells, etc.) and battery materials / components, etc.). Research and development corporation by field (environment / energy, life science, system / information science and technology, nanotechnology / materials) Hardware / software development using cutting-edge technology, demonstration experiments, research / development / operation / sales of prototype products, By research field (environment / energy, life science, system / information science and technology, nanotechnology / materials) Cutting-edge technology research development 5 research fields (cluster) "Future Society / Future Technology (Science 5.0 Social Implementation)" "Next Generation Food and Planting" "Environment / Energy / Regeneration" "Health / Longevity / Development" "Creation of Knowledge"
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Task
Food Loss CO2 Emission Reduction Protein Crisis Super Aging Society / Inclusive Food Experience Labor Shortage (Utilization of Robots) Healthy Eating New Normal Service Food Manufacturing Factory, Logistics, Retail Smart Agritech
Graduate School of Advanced Science and Technology Information Area Technology
Agri-Bio Drug Discovery Medical / Welfare Environment Energy Manufacturing Technology Material Device / Equipment Machinery Construction / Civil Engineering Electronic Communication Information Measurement
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CEO YuHongHong
Certified accountant Tax accountant, patent attorney, labor and social security attorney, artificial intelligence researcher
Tsinghua University Visiting Professor.Born in 1970, Ph.D. in Computer Science, Harvard University, 35 years of management and cutting-edge science and technology experience .currently the head of NTT DATA PM
a researcher of artificial intelligence, a scholar of the Chinese Academy of Sciences, a regular member of the JSAI Society for Artificial Intelligence, a member of IEEE, a member of SIGIR, a member of the CAAI China Artificial Intelligence Association, a member of the AAA1 International Artificial Intelligence Association, British Artificial Intelligence A member of the ACM, a member of the Chinese Society for Artificial Intelligence, and his main research fields are ERP consulting, cloud technology, big data, blockchain, artificial intelligence specialists, computer vision, multimedia technology, machine learning, etc.
He is a visiting professor of machine learning at Tsinghua University. Fusion with technology megatrends, state-of-the-art analytical technology includes government / local government, education / medical / healthcare, finance, manufacturing, logistics, telecommunications / broadcasting, construction / real estate, electricity / gas / water, networking, pharmaceuticals Used in agriculture, retail, manufacturing, transportation, sports, aerospace, advertising, IOT, ICT and other industries. Harvard Business School Visiting Professor, Tsinghua University Computer Science Visiting Professor, University of Tokyo Visiting Professor, University of Tokyo Visiting Professor, Osaka University Visiting Professor, Kyoto University Visiting Professor, China Science and Technology Association, Jiangsu Province Z Jiang Provincial Government Organized Contest Category A Wins First Prize Large Health Industry: Biomedical, medical equipment, smart medicine, health management, etc. received the highest award in Category A. ERP Blockchain Cloud Technology Big Data Artificial Intelligence-related fields (not limited to the field of voice processing including various fields of artificial intelligence) won the highest award in the patented product competition, Ali, Tencent, Huawei and other contracts And reached a number of contracts. AI x 5G Face Brushing has become the mainstream payment method, WYSIWYG, Short Video AI Animation x 5G, AR VR and 3D, Intelligent Driving, Finance, 5G Remote Medicine 5G AI Medicine, Intelligent Driving Intelligent Business Intelligent Medical Public Security 5G robots 5G materials, semiconductors, sports, entertainment and other technologies are our mainstream technologies, separation and purification, innovative pharmaceuticals, biotechnology, chip design, quantum dot display, multi-touch, nanomicrospheres, low carbon World-leading intelligent driving, smart manufacturing, robotics, and smart medical with key technologies for nanomaterials. Face and human body analysis technology, SLAM and 3D vision, general and professional image recognition, robot control and sensing, large-scale video understanding and mining, image and video processing to enhance medical image analysis, artificial intelligence computing Platform, AI supercomputing platform, self-developed training framework, AI high-performance storage High-performance heterogeneous computing software and hardware combined with state-of-the-art artificial intelligence algorithms and chip design capabilities Design and develop high-performance, low-cost, low-power edge artificial intelligence chips and solutions to openly enhance your partners. For intelligent driving and AIoT, we can provide edge-to-edge AI chips with ultra-cost performance, extreme power efficiency, open toolchains, rich algorithm model samples, and comprehensive activation services. Today, BPUs (Brain Processing Units) based on innovative artificial intelligence-specific computing architectures are being streamed successfully. China's first edge artificial intelligence processor-a system focused on intelligent driving and a system focused on AIoT. And it has been commercialized on a large scale. Member Science Agency of the British Association of Artificial Intelligence and the Technical Committee of the British House of Representatives (Science and Technology Committee of the House of Representatives) British Council on Artificial Intelligence Open Data Institute (ODI) Alan Turing Institute, University of Cambridge, University of Edinburgh, University of Oxford, London Including EPSRC Association of Universities, University of Oxford
State-of-the-art technology for AI, IoT, RPA, OCR-AI, ERP, cloud, big data, blockchain, ICT, 5G, 3D, AR, VR, iCLIP, core industrial software, core algorithms, neutrinos, government / local governments Education / Medical / Healthcare, Finance, Manufacturing, Logistics, Communications / Broadcasting, Construction / Real Estate, Electricity / Gas / Water, Networks, Pharmaceuticals, Agriculture, Retail, Manufacturing, Transportation, Sports, Aerospace, Advertising, IOT, ICT and Other industries
IEEE, NIPS, ICML, COLT, CVPR, ICCV, ECVC, IJCAI, AAAI, UAI, KDD, SIGIR, WWW, ACL, PAMI, IJCV, JMLR, AIJ have been published more than 100 times.


Motto
Motivation-Driven
Learn or Die
Proud, but Humble
Boldly do what no one has done before

Harvard University, Oxford University, Cambridge University are the leading research and academic fields in the field of top doctoral professors. The technology R&D team has more than 380 people.
The characteristics of the team are graduates from prestigious schools, background in science and engineering, management elites, Silicon Valley, Harvard, MIT, Oxford and Cambridge, and clear thinking. Relying on technological innovation, advanced management, high barriers to entry, establishing network effects, brand effects, patented technologies and scale effects, competition is prepared for losers, and we can do business that other companies simply cannot do. Determine our CAC/LTV ratio (that is, the user acquisition cost/user lifetime value ratio of paid marketing) and continue to increase this ratio. Establish our core competitiveness. The niche market has explosive growth. Our team has successfully cooperated with the team for more than 10 years. The profitability data of market traction is rising.Successful funding from Google, Amazon, Apple and Arm provided 13 million pounds for its probabilistic modeling platform. Professor Steve Young from the development team of the University of Cambridge in Cambridge, and the team of Professor Guolong in Information Engineering
Official member of JSAI Artificial Intelligence Society, IEEE member, SIGIR member CAAI Chinese Artificial Intelligence Society member, AAA1 International Artificial Intelligence Society member. A member of ACM, the British artificial intelligence Chinese ACM Specialist, his main research areas include ERP consulting, cloud technology, big data, blockchain, artificial intelligence experts, computer vision, multimedia technology and machine learning.
AI, IoT, RPA, OCR-AI, ERP, cloud, bigdata, blockchain, ICT, 5G, 3D, AR, VR, iCLIP, core industrial software, smart chips, smart driving, core algorithms, neutrinos, quantum artificial intelligence And other top cutting-edge technologies. For government/local government, education/medical/healthcare, finance, manufacturing, logistics, communications/broadcasting, construction/real estate, electricity/gas/water, network, pharmaceutical, agriculture, retail, manufacturing, transportation, sports, space Aviation, advertising, IOT, ICT and other industries. AI journalist sports intelligent driving AI accounting lawyer AI surgical robot AI consultation Misdiagnosis no ai robot funeral VR AR 3D AI crime tracking AI image recognition
IEEE, NIPS, ICML, COLT, CVPR, ICCV, ECCV, IJCAI, AAAI, UAI, KDD, SIGIR, WWW, ACL, PAMI, IJCV, JMLR, AIJ have continuously published more than 1,000 top academic papers. The artificial intelligence competition won 500 awards. More than
With the world's leading AI, IoT, RPA, OCR-AI, ERP, cloud, bigdata, blockchain, ICT, 5G, 3D, AR, VR, iCLIP, core industrial software, core algorithms, neutrinos, quantum artificial intelligence, intelligence Driving, smart chips and other top core technologies, these core technologies all come from independent research and development, with independent intellectual property rights. Actively advocate sunshine and health
The corporate values of the business philosophy, compliance with applicable laws and regulations, product technologies are widely used in smart chips, education, healthcare, finance, sports, security, new retail, unmanned driving, robots, IOT, ICT, smart manufacturing, smart transportation, smart cities , Smart home, smart management, RPA, smart factories, smart logistics, nano new materials, new energy, carbon neutrality, environmental protection, SDGs, EDG, and other social inclusive fields
The company has strong own capital and believes in a geek culture. The core team members are all industry elites with senior R&D and management experience from Google, Amazon, Facebook, IBM, Microsoft, Nvidia, Huawei, Tencent, and Alibaba. Computer software, computer technology, network technology, network technology, aerospace construction technology, 3D printing technology, etc. Our scientist The famous deepmind top scientist is also the chief scientist of Google, From Google, Amazon, Apple and Arm successful £13million funding round for its probabilistic modelling platform. Professor Steve Young information engineering at the University of Cambridge development team based in Cambridge ".
The technology held by the leading scientists and professors of the leading scientist team of the Microsoft Cambridge Research Institute in the United Kingdom: financial information analysis technology, biomedical data analysis technology, DNA cell analysis technology, Internet of Things data analysis technology, motion behavior analysis technology, face Ministry of Recognition and Analysis Technology, Skeleton Analysis Technology, Manufacturing Automation System, Automatic Design Model Technology, Cloud System, Cultural Education System
Such as carrying out special case studies related to advanced biomedicine. Specific predictive analysis methods authorized by data science and artificial intelligence. .Top 100 AI drug discovery and advanced medical field leaders" (PDF) research scientist, clinician and technical expert in academia, pharmaceutical companies and artificial intelligence companies. The winners include CSAIL principal investigator and MIT professor Regina Barzilay, Tommi Jaakkola, Manolis Kellis and Peter Szolovits. etc.
Example: Treatment of infertility AI technology medical big data analysis, now it can treat azoospermia. The method of making surviving sperm into the human body. AI technology medical big data analysis, now it is possible to make the surviving sperm into a chip and implant it in the human body. The method can be cured.
Signed a cooperation agreement with Zhejiang Enze Hospital's anti-cancer "magic drug" research cooperation, the world's top scientist-Randy Wayne Shekman 2013 Nobel Prize in Physiology or Medicine, a famous American cell biologist , Enze Hospital, a member of the National Academy of Sciences, developed by Taizhou Pharmaceutical Enterprise http://www.enzemed.com/jtjs/index.html
https://www.blog.google/products/pixel/new-features-pixel4/ Google’s technology is currently possible for Huawei, and Huawei has signed a contract with Harbin Niuqiao.
Harniu Bridge is a team based in the United States and the United Kingdom, and Google's technology is also one of the main cores of our team, which is a strong alliance. https://www.nikkei.com/article/DGXMZO48438220Z00C19A8MM8000/
https://www.liverpoolfc.com/ British Liverpool team signs Smart Sports
Japan's asteroid space exploration AI, Kyoto University's medical AI big data analysis won the 2018 Nobel Prize, and intelligent translation is used in search engines. At the beginning of the establishment of the Institute, the company actively deployed artificial intelligence, blockchain and other cutting-edge fields, and established various module laboratories in Nanjing, Shanghai, Hangzhou, Suzhou, and Taizhou. We uphold the concept of technology first, products for use, relying on strong technical strength, while connecting and cooperating with universities and scientific research institutions at home and abroad, continue to innovate, strive for excellence, output first-class research results in the industry, and actively embrace the market and combine User experience to create high-quality commercial products.
With Microsoft, Microsoft Cambridge Research, IBM, Samsung, H2o, Google, Intel, HP, intel, Amazon, CAPCOM, Domo, MonotaRO Co., Ltd., Kubota Machinery, SCSK Co., Ltd., Kubota Co., Ltd., Komatsu Machinery, Shimizu Construction, Ali Baba, Hang Seng Electronics, Yahoo, Tencent, Huawei, Facebook Paris Research Institute, SAP, Oracle, salesforce, British Liverpool team and Li Ning Sports, Ali Sports, momenta, Super Sports XEBIO Sports Goods Physical store, TikTok (TikTok Douyin), NVIDIA, NTT, NTTDATA, Softbank, Samsung DIDI Smart Driving, freee Co., Ltd., Abam Co., Ltd., ARTNER Co., Ltd., DeNA Co., Ltd., American Industrial Co., Ltd. Robot Intelligent Robot Boston Dynamics, Toshiba Intelligence System Co., Ltd., Hitachi, NEC, TOYOD, Mitsubishi Group, Mitsui Group, TIS, KONAMI, PWC, Accenture Consulting, BearingPoint Consulting, Capgemini-Ernst & Young Consulting, Deloitte Consulting, IBM Consulting, sas, Haoop, matlab, Tableau Kobayashi Pharmaceuticals, Suning Group, JD TOYODA Honda SenseTime (SenseTime) despise Yitu Momenta Horizon Fourth Paradigm, Qualcomm, Philips, Siemens, Sony, Intel, Canon and other famous companies have contracts. R&D Center China Nanjing Headquarters, Hangzhou Headquarters, Shanghai Headquarters, Taizhou Branch, Lishui Department, Suzhou Branch, etc., Japan, the United Kingdom, the United States, Germany, South Korea, etc.
Based on the original technology system, the AI deep learning platform is the core "brain" quantum computing cloud and other cutting-edge technologies as the guide, the layout of multi-field, multi-directional cutting-edge research, and quickly get through the application of AI and other cutting-edge technologies in various vertical scenarios.
Research has always adhered to originality, continuous breakthroughs and innovations, and has established in-depth cooperative relationships with dozens of first-class universities and research institutes at home and abroad. It has deep academic accumulation in the field of artificial intelligence and a sound talent training mechanism. The Harvard Graduate School of Design, Harvard University School of Design, is considered to be one of the best design schools in the world. Cooperation with Harvard University, Cambridge University, Oxford University MIT, Tokyo University, Kyoto University, Osaka University, Tsinghua University, Chinese Academy of Sciences, etc.
The development team is composed of top AI application technology experts from China, the United States, the United Kingdom, and Japan. It has successfully developed a series of projects such as deep learning training platforms, distributed data storage, global supercomputing centers, edge computing products, and technical communities. It has gathered more than 30,000 AI developers and enthusiasts from major universities and companies around the world. Begin the process of internationalization, radiate European and American countries with the US subsidiary as the core, and use the regional advantages of the British Singapore subsidiary and Hong Kong subsidiary to drive the development of Southeast Asian markets such as Taiwan, Malaysia, Indonesia, and Thailand.
R & D Engineering Center
• Patent invention
• Product Center
• Product Center
• Patented technology:
• Financial information analysis technology,
• Biomedical data analysis technology,
• DNA cell analysis technology,
• Internet of Things data analysis technology,
• Movement behavior analysis technology,
• Facial recognition analysis technology,
• Bone analysis technology,
• Manufacturing automation system,
• Automatic design model technology,
• Blockchain cloud system,Quantum computing supercomputing platform
• Cultural education system, etc.



CTO Guo Long
Certified accountant Tax accountant, patent attorney, labor and social security attorney, artificial intelligence researcher、Oxford University Professor、doctor.
10 years of management and cutting-edge science and technology experience .currently the head of NTT North American Laboratories PM
Born in 1995, Ph.D. in Computer Science, The University of Cambridge
Leverhulme Centre for the Future of Intelligence,LCFI
Guo Long, born in July 1995, is a researcher of the Chinese Academy of Sciences, a full member of the JSAI artificial intelligence society, an IEEE member, a SIGIR member, a CAAI member of the Chinese artificial intelligence society, and a member of the AAA1 international artificial intelligence society. Member of ACM, British Artificial Intelligence China Member of ACM CAAI Member of China-Britain Artificial Intelligence Association
The main research areas include ERP consulting, cloud technology, big data, blockchain, artificial intelligence experts, computer vision, multimedia technology and machine learning. Dr. Cambridge Professor Oxford University
Guolong The University of Cambridge PhD
Leverhulme Centre for the Future of Intelligence, LCFI http://www.lcfi.ac.uk/Chief Scientist, Top Research Institute, LCFI Labs, UK
He holds a Ph.D. in Computer Science from the University of Cambridge, a professor at the University of Cambridge, and a CTO. Leader in cutting-edge technology. AI, IoT, RPA, OCR-AI, ERP, cloud, bigdata, blockchain, ICT, 5G, 3D, AR, VR, iCLIP, core industrial software, core algorithms, neutrinos, quantum artificial intelligence and other top cutting-edge technologies.
High school studying in the UK, undergraduate, master's degree at Cambridge University, in 2017 received a PhD in computer science from the University of Cambridge, UK. So far, as the project leader, he has conducted research and development in 863 major projects, sub-projects of the National Science and Technology Support Program, and projects of the National Natural Science Foundation of China, and has published 12 papers including SCI and 28 papers from EI . Collected 29 articles and obtained multiple invention patents. At present, the Institute of Information Science of the Chinese Academy of Sciences offers basic courses "Computer Vision and Image Understanding" and professional basic courses "Modern Computer Vision". Deep Tech focuses on the integration of AI, blockchain big data analysis cloud, ERP consultants and technology megatrends. Drug discovery in Eastern Europe, fintech and blockchain, fintech and blockchain in Asia. 5 core technologies-biometrics, artificial intelligence, chatbots, data analysis, blockchain. 4 sub-sectors: loans, payments, savings, insurance. Conduct special case studies related to advanced biomedicine. Data science and AI enhance specific methods of predictive analytics. For the specific vision we use to design investment strategies and work with strategic partners, advanced forecasts focus on the convergence of the DeepTech industry. Research scientists, clinicians and technicians in academia, pharmaceutical companies and AI companies. Our team includes Dr. Tasuku Honjo, Dr. Yusuke Honjo, Nobel's PD-1 Physiology, CSAIL's lead researcher, MIT Regina Barzilay, Tommi Jaakkola, Manolis Kellis and Peter Szolovits.
The main research areas are ERP consulting, cloud technology, big data, blockchain, artificial intelligence experts. The person in charge has undertaken research and development work on 863 key projects, sub-projects of the National Science and Technology Support Plan, and National Natural Science Foundation projects. More than 510 scientific papers, of which 50 are included in SCI, 60 are included in EI, 129 are included in ISTP, and 225 invention patents have been obtained
For example, computer vision, multimedia technology, machine learning, Tsinghua University professor. Convergence with technology megatrends, leading analytics technologies are used in government / local government, education / medical / healthcare, finance, manufacturing, logistics, communications / broadcasting, construction / real estate, electricity / gas / water, networking, pharmaceuticals , Agriculture, retail, manufacturing, transportation, sports, aerospace, advertising, IOT, ICT and other industries.
AI reporter sports intelligent driving AI accounting lawyer AI surgical robot AI interrogation misdiagnosed AI robot funeral VR AR 3D AI crime tracking AI image recognition. China Science and Technology Association, Jiangsu Province, Zhejiang Provincial People's Government hosted the contest and won the first prize in category A. Big health industry: Biomedicine, medical equipment, smart medicine, health management, etc. won first prize in category A.
His main research fields are computer vision, big data blockchain, and natural language processing. Chief Technology Specialist of Alibaba Group
Rugby 5G technology invented by AI deep learning (one of the artificial intelligence (AI) technologies used for image recognition and speech recognition) Developed a rugby game analysis system that combines deep learning, shooting human movements with a camera, and measuring the body passing by AI Posture and movement, AI-guided 5G technology
Professor of Machine Learning at Tsinghua University. Integration with technology megatrends, cutting-edge analytical technologies, government / local government, education / medical / healthcare, finance, manufacturing, logistics, communications / broadcasting, construction / real estate, power / gas / water, networking, and pharmaceuticals for agriculture, Retail, manufacturing, transportation, sports, aerospace, advertising, Internet of Things, ICT and other industries. Professor A of Cambridge University, Visiting Professor of Computer Science at Tsinghua University, and Visiting Professor of Chinese University of Science and Technology, Jiangsu Province, Kyoto University, won the first prize of the big health industry in the competition category A: biomedical, medical equipment, intelligent medicine, health care, etc. Won Category A Best Award. ERP blockchain cloud technology big data artificial intelligence-related fields (not limited to the field of speech processing including artificial intelligence fields) won the highest award in patent product competitions, Ali, Tencent, Huawei and other contracts and reached many contracts. AI x 5G face brushing has become the mainstream payment method, WYSIWYG, short video AI animation x 5G, AR VR and 3D, smart driving, finance, 5G telemedicine 5G AI medicine, smart driving, smart commerce, smart commerce, smart Medical, public security 5G robots, 5G materials, semiconductors, sports, entertainment and other technologies are our mainstream technologies, separation and purification, innovative drugs, biotechnology, chip design, quantum dot display, multi-touch, nano-microspheres, low carbon Global key technologies for nanomaterials smart driving, smart manufacturing, robotics and smart medical. Face and body analysis technology, SLAM and 3D vision, general and professional image recognition, robot control and sensing, large-scale video understanding and mining, image and video processing to enhance medical image analysis, artificial intelligence computing platform, artificial intelligence supercomputing platform , Self-developed training framework, artificial intelligence high-performance storage By combining high-performance heterogeneous computing software and hardware, high-performance, design and develop low-cost, low-power edge artificial intelligence chips and solutions to develop partners. For intelligent driving and AIoT, it can provide edge-to-edge AI chips with super high cost performance, high energy efficiency, open tool chain, rich algorithm model samples, and comprehensive activation services. Now, BPU (brain processing unit) based on innovative artificial intelligence-specific computing architecture is successfully streaming. China's first edge artificial intelligence processor-a system focused on intelligent driving and a system focused on AIoT. And it has been commercialized on a large scale. Member of the Chinese Academy of Artificial Intelligence, a member of the British Science Bureau and a member of the House of Science and Technology Committee, the House of Commons (Science and Technology Committee), Allen Turing Institute for Artificial Intelligence, Open Data Institute (ODI), Cambridge University, University of Edinburgh, University of Oxford, University of London, including University of Warwick EPSRC
Suitable for AI, IoT, RPA, OCR-AI, ERP, cloud, big data, blockchain, ICT, 5G, 3D, AR, VR, iCLIP, core industrial software, core algorithms, neutrinos, government / local government State-of-the-art technology education / medical / healthcare, finance, manufacturing, logistics, telecommunications / broadcasting, construction / real estate, electricity / gas / water, networking, pharmaceuticals, agriculture, retail, manufacturing, transportation, sports, aerospace, advertising, physical Internet, ICT and other industries
IEEE, NIPS, ICML, COLT, CVPR, ICCV, ECVC, IJCAI, AAAI, UAI, KDD, SIGIR, WWW, ACL, PAMI, IJCV, JMLR, AIJ have been published more than 100 times.
work experience
Dr. Guolong The University of Cambridge Cambridge
Leverhulme Centre for the Future of Intelligence, LCFI http://www.lcfi.ac.uk/Chief Scientist, Top Research Institute, LCFI Labs, UK
AlibabaGroup contract unit HOC Intelligent Technology Guolong Deputy General Manager CTO
Professor of computer vision, multimedia technology, machine learning, Tsinghua University. Convergence with technology megatrends, leading analytics technologies are used in government / local government, education / medical / healthcare, finance, manufacturing, logistics, communications / broadcasting, construction / real estate, electricity / gas / water, networking, pharmaceuticals , Agriculture, retail, manufacturing, transportation, sports, aerospace, advertising, IOT, ICT and other industries.
AI reporter sports intelligent driving AI accounting lawyer AI surgical robot AI interrogation misdiagnosed AI robot funeral VR AR 3D AI crime tracking AI image recognition. China Science and Technology Association, Jiangsu Province, Zhejiang Provincial People's Government hosted the contest and won the first prize in category A. Big health industry: Biomedicine, medical equipment, smart medicine, health management, etc. won first prize in category A.
His main research fields are computer vision, big data blockchain, and natural language processing. Chief Technology Specialist of Alibaba Group
Rugby 5G technology invented by AI deep learning (one of the artificial intelligence (AI) technologies used for image recognition and speech recognition) Developed a rugby game analysis system that combines deep learning, shooting human movements with a camera, and measuring the body passing by AI Posture and movement, AI-guided 5G technology
JSAI Artificial Intelligence Society Regular Member https://www.ai-gakkai.or.jp/
CiNii Articles: http://ci.nii.ac.jp/
CiNii Books: http://ci.nii.ac.jp/books/
CiNii Dissertations: http://ci.nii.ac.jp/d/
Scientific Research Grants Support Business | Japan Society for the Promotion of Science
https://www-shinsei.jsps.go.jp/kaken/index.html
Scientific research grants help undertakings-Scientific research costs-: Ministry of Education, Culture, Sports, Science and Technology
http://www.mext.go.jp/a_menu/shinkou/hojyo/main5_a5.htm
Government Office of Science and UK House of Commons Science
The Technical Committee (The House of Commons ’Science and Technology Committee)
British Council on Artificial Intelligence
Open Data Institute (ODI)
Including the Alan Turing Institute and the EPSRC Association of Cambridge University, Edinburgh University, Oxford University, University of London, University of Warwick
https://www.caai.cn/Chinese Association for Artificial Intelligence
Member of AAA1 International Artificial Intelligence Association






























As a network-type science research institute that conducts world-class research and development, we will lead SDGS future co-creation ICT company sustainability innovation. Science and Technology Research and Development Corporation UK, Canada, US, Germany, Japan, China We will create and support our bases together to develop and provide cutting-edge science and technology products with high quality and unique technology, and open up a prosperous future. increase. AI (application of face recognition, deep learning, etc.) IoT 5G blockchain Quantum computing DX biotechnology such as XR, AR, VR Obtained many patents on cutting-edge technology and development, and will continue to utilize cutting-edge technologies such as "ICT companies" We support research and demonstration experiments, plan services and products in new technology areas, and demonstrate concept models. Industry-academia-government collaboration "Connecting cutting-edge technology and business" Research and research in the field of cutting-edge technology System consulting solution service Product solution We support companies that do their best to overcome the corona disaster! New medical technology developed in an integrated project centered on six modalities (pharmaceuticals, medical devices / healthcare, regeneration / cells / gene therapy, genome / data infrastructure, disease basic research, seeds development / research infrastructure), etc. Is effectively deployed for various diseases. In addition, there are six research and development related to the disease fields (cancer, lifestyle-related diseases, psychiatric / neurological diseases, geriatric medicine / dementia, intractable diseases, growth, infectious diseases, etc.) that will be social issues in Japan now and in the future. It is promoted across the integration project under the executive control of the program director (PD) and disease area coordinator (DC) of the integration project. Research Organization of Information and Systems Informatics Research Institute is the only research institute in Japan whose mission is to create future value in the new academic field of informatics. Aiming for basic research from a long-term perspective and solving social issues in a wide range of research fields, from basic theory in informatics to cutting-edge themes such as artificial intelligence, big data, the Internet of Things (IoT), and information security. We are promoting practical research.
In addition, as a university joint research and development, we will work on the construction and operation of academic information infrastructure that is indispensable for research and educational activities of the entire academic community, including the academic information network infrastructure, and develop businesses such as providing academic content and service platforms. I am developing. Furthermore, by mutually feeding back the knowledge obtained through the business and the knowledge obtained from the academic research, we are conducting academic research that responds to actual issues and businesses that utilize cutting-edge technology.
Through these activities, we strive to develop human resources and contribute to society and internationally, and we also focus on cooperation and cooperation with private companies and various social activities as well as universities and research institutes in Japan and overseas. In addition, we are also engaged in graduate school education aimed at promoting original and international academic research and developing leading academic fields.
In order to support a wide range of academic fields such as informatics, we have established four research systems, "Informatics Principle Research System", "Architecture Science Research System", "Content Science Research System", and "Information Society Correlation Research System", and applied from the basics. We are doing unique research up to. Informatics Principle Research System
In addition to pursuing new principles and theories of informatics such as algorithms and computational complexity theory, artificial intelligence, robotics, quantum computing, etc., we are conducting research with the aim of developing new technologies and developing new fields that will support future society. I am. field of study
Algorithms, artificial intelligence, machine learning, deep learning, big data analysis, data mining, mathematical modeling, numerical analysis, computational science, web informatics, neuroscience, quantum information, and new principles and theories related to these boundary areas, etc. Advanced research that creates possibilities for new applications
Architecture Science Research System
Aiming for higher performance, higher quality, and higher functionality of computers and networks, which are the basic elements of information technology, we are establishing innovative technologies in software and hardware architectures and implementing practical systems. field of study
Research and development on post-Internet, cyber security basics, software / hardware architecture, distributed / cloud computing, programming languages, system performance / log analysis infrastructure, dependent systems, Internet of Things (IoT), network / cloud visualization
Content science research system
Research on content such as symbol media and pattern media and analysis / generation of media, research on basic technology for accumulating / searching / organizing content, research on interaction and social media analysis focusing on humans and knowledge. And so on. field of study
Research and development on the development of natural language processing, computer vision, image processing, acoustic information processing, computer graphics, databases, human interaction, web mining, social media, community analysis, media clone generation / recognition, machine learning / deep learning applications, etc.
Information Society Correlation Research System
In a cyber-physical fusion society where the information world and the real world are integrated and linked, information / system technology for making rational decisions based on scientifically-based data and interdisciplinary human science / social science I am doing a lot of research.
field of study
Privacy Information protection and utilization, next-generation anonymization, data governance, next-generation IR infrastructure theory, data policy theory, data utilization human resource development theory, digital humanity, IT healthcare, data reliability evaluation, cloud sourcing, digital education , Research and development on open innovation infrastructure, and research on humanities and social science related to these topics










Personalized medicine, regenerative medicine, genome. Extension of healthy life expectancy by medical technology, biopharmacy, etc. Advancement of prevention, advancement of AI, high performance of robots in the technology field
Utilization of AI and robots in dementia care and long-term care
Technology development for a society that does not cause dementia that can be prevented
About efforts in the field of cancer genomic medicine and artificial intelligence care / dementia
Nursing robots provide nursing care services. Smart laboratories. Health management utilizing AI. AI assists doctors ... Medical care and nursing care in Japan, which is facing the world's first rapidly aging society.
Utilization of AI. Dementia care. Self-support. Prevention of aggravation. Status of need for long-term care, etc. Maintenance / improvement. Health / medical care / long-term care. ・ Data such as rehabilitation / nutrition ... Brain science. Actuators that drive robots Nursing robots provide nursing care services. Smart workplaces. Health management utilizing AI. AI assists doctors ... Japan is welcoming the world's first rapidly aging society In the reform of medical care and long-term care
AI-equipped robots guide conversations in elderly groups to prevent dementia-Healthcare AI Development Acceleration Consortium
Supporting medical care and long-term care with AI x robot arm
"It was developed by combining AI (artificial intelligence), biomechanics, and ergonomics. It is a robot that has visual and tactile sensations and can imitate the delicate movements of human fingers.
Robot arms are generally used on production lines. If it is applied to long-term care or rehabilitation, it must break through the hurdle of having delicate movements like human fingers. The ultra-regional research team has developed a robot that combines AI (artificial intelligence), biomechanics, and ergonomics to have visual and tactile sensations and to mimic the delicate movements of human fingers. It can hold the ball and remove the tissue like a human. Designed to imitate the joints of human fingers, it bends the fingers by transmitting air pressure. In addition, the repulsive force received by the fingers by the arithmetic chip using the patented technology of the United States is measured by the sensor, and the survey is performed at an accurate angle. Generally, when a robot grabs a ball or grabs a bottle of beverage, it mechanically opens and closes its five fingers to grab or grab an object. However, it has a human-like smoothness. This is because human movements were digitized and the robots learned them little by little. If both hands can be moved like humans, robots will be able to hold babies, rub the backs of sick and old people, and raise their bodies in the future.
In addition to the delicately movable fingers, the team made a seven-axis robot with zero blind spots. This has a wider range of movement than a general 6-axis robot. You can bend your arms to an angle that humans cannot reach. In addition, because it has a freely movable neck and a 3D stereoscopic visual system, it is possible to scan surrounding objects in a wider range. In other words, it has a sense of "space." Moreover, it is possible to identify things by AI.
The part corresponding to the "brain" of the robot was researched and developed mainly by Professor Tatsu Kinnaka, Associate Professor Huang Ji, Associate Professor Zhu Hongkuni, Professor Seifumi Wu of Electrical Engineering, and Professor Yasushi Liu. Various breakthroughs in research and development that have won the "FutureTech Breakthrough Award" and the "National Innovation Award" have been applied so far.
What is the possibility of creating a combination of technology and "tactile sensation," which has many unexplained parts of the five human senses?
Listen with your skin. Haptics, a tactile information transmission technology, is attracting a lot of attention. In addition to the tactile reproduction already implemented in game controllers, various applied research such as remote surgery machines and alternatives to Braille is in progress. Facebook, which has launched an innovative approach in this field, is exploring the future of SNS that conveys symbolized emotions such as "likes" by stimulating the skin.
I have been studying tactile sensation at university for nearly 20 years. However, the general reaction is that we do not know what tactile research does. In fact, in recent years, a technology called "Haptic" (meaning "tactile"), which gives tactile feedback through vibration and movement, has been attracting attention, and Facebook is showing its presence in this field.
Research on human senses can be broadly divided into three fields.
One is the physiological field of investigating how people perceive the outside world using their senses.
The second is the field of sensors that artificially detect information with a mechanism similar to humans.
The third is the field of artificially presenting such a feeling.
Taking "vision", which is the most studied of the five senses, as an example, the physiological cells on the retina that are sensitive to the three primary colors of RGB (red, green, and blue) respond to each component of light. The first field is research on various parts and research that clarifies people's perceptions when they see various patterns of stimuli.
And the second is to make a camera by artificially realizing such basic performance.
The third field corresponds to making displays and projectors that present the images recorded in this way.
Tactile research is basically the same as these. "Elucidate the sensor of human skin sensation" "Realize sensing that gives the surface of the robot a tactile sensation similar to human" "Reproduce the sensation artificially by presenting an appropriate vibration / pressure pattern" Research is being conducted all over the world on themes such as.
Tactile research that is also used in Nintendo Switch
Then, in what fields can such tactile technology be used?
For example, the vibration of smartphones can be said to be the result of widespread tactile research. In recent iPhones, instead of physically pressing the button, by reproducing an appropriate vibration pattern, you can reproduce the feeling of clicking.
In recent years, game companies have been particularly focusing on tactile research, making use of it in controller functions. In Nintendo Switch, it is called "HD vibration" and appeals that it has a high definition (HD: High Definition) tactile sensation. With software called "1-2-Switch," there are games that you can enjoy just by vibrating, making use of the tactile sensation of the controller. DualSense, the PlayStation 5 controller, is talking about new features such as "haptic feedback" and "adaptive triggers." The tactile sensation is utilized in the form of generating a force that pushes the button back, improving the immersive feeling in the game.
An example of the research stage is an application such as a remote surgery machine. In endoscopic surgery, operations such as removing a tumor by controlling forceps from a distance, relying on images, are performed. At that time, by tactilely feeding back the force applied to the forceps, it is expected to have effects such as intuitively understanding whether other organs are damaged and improving the operability of the forceps. NS.
These are examples of reproducing the tactile sensation felt by humans, but there is also an application of transmitting symbolic information to humans via a channel called tactile sensation.
Braille is the easiest way to convey symbolic information by touch. The blind person can understand the character information by touching the uneven pattern through the tactile sense. However, there are not so many visually impaired people who can read Braille, and a 2006 survey by the Ministry of Health, Labor and Welfare reported that the percentage of visually impaired people who answered that they could read Braille was 12.7%. Braille is not always indispensable because some visually impaired people have low vision such as amblyopia and narrowing of the visual field, and more recently, machine-based text-to-speech technology has become widespread. However, the penetration rate of Braille as a visual alternative information acquisition channel is by no means high.
About this, some research has been done on whether it is possible to convey textual information via tactile sensation without training. A previous study in our laboratory found that if you hold a pen and the pen moves to write letters automatically, the person holding the pen can recognize the text information with considerable accuracy. .. It has been confirmed that the 26 letters of the alphabet can be understood with an accuracy of 90% or more at a pace of one letter per second.
"Typing with the brain and listening with the skin"
Facebook is actively researching the transmission of symbolic information via such tactile sensations. At the world Haptics, the largest international conference in the field of tactile sensation held once every two years, the company ranked first in the 2019 paper acceptance ranking by institution. The number is twice as large as that of the University of Tokyo, which ranks second. At the 21-year conference held the other day, although the number of presentations was small, probably due to the influence of the corona disaster, there is no doubt that he is focusing on tactile research.
Facebook first received a lot of attention in tactile research with the two approaches of "typing with the brain" and "listening with the skin" advocated in 2017. If we think of human beings as a "system that inputs and outputs some information," most of the information output is via voice, fingers, or a keyboard. On the other hand, most of the information input is audiovisual. It is either input through the eyeball by a two-dimensional color and light / dark pattern, or input as sound through the vibration of the eardrum.
Facebook's idea is to input and output this information on a different channel than before.
Regarding the "output" of information, it seems that they are thinking of reading the brain signal directly and outputting it as information without making a voice or moving their hands. This is the aforementioned "typing in the brain", but it is also a topic that has been widely studied in the field of Brain Machine Interface (BMI). For example, for patients with diseases such as ALS (Amyotrophic Lateral Sclerosis) that make it impossible to move the muscles of the whole body, there is an application that sends out one's intention to the outside just by thinking in the head. It has been considered. Recent advances in artificial intelligence (AI) and machine learning technology have made it possible to appropriately analyze measured EEG patterns. Around the same time as Facebook's proposal, Elon Musk, the founder of Tesla, a major US electric car maker, is proposing "Neuralink," a capacity expansion by implanting electrodes in the brain.
On the other hand, "input" strongly reflects our lifestyle as to which of the two information channels, visual and auditory, is used. For example, in the United States of the automobile society, information transmission using voice channels such as podcasts is popular. When driving, only hearing is available, and we are aiming for that. On the other hand, in urban areas of Japan, many people use trains when commuting to work or school. Since it is safe to occupy the visual sense on the train, it is more efficient to obtain information visually such as characters and images.
Facebook's aim is to use tactile sensation as a new channel here. Tactile sensation is a sensation that is widely distributed throughout the body. Since the four senses of sight, hearing, smell, and taste have localized sensory organs such as eyes, ears, nose, and mouth, it is difficult to present further information if they are occupied by some stimulus. .. In the case of tactile sensation, even if the handle is held by hand, there are still many unused areas such as arms, shoulders, abdomen and thighs. By giving an appropriate stimulus here, for example, if you can convey information as if you were listening to voice with your ears, you may be able to check the title of the incoming mail even while driving a car and listening to music. be.
Do you convey your feelings just by touching?
When I read the article "Listen on the skin" in 2017, I was most interested in how much information could be transmitted through the skin. I thought that the sense of touch was not smart enough to convey precise textual information. Opening of the anime "Lupin III" There is a production in which subtitles are displayed character by character like a flash, but many people may find it difficult to read. Similarly, when the tactile sensation was displayed symbolically one by one, I thought it would be difficult to connect them in the time direction and understand them as sentences.
The results of Facebook announced at World Haptics in 19 were exactly the answers to this question based on two years of research. In a word, the content was that it did not assume the transmission of precise text information.
So what were you trying to hear on your skin? It is "emotion". In one study, one subject was instructed to keep his arm out and another subject to touch her forearm to convey a particular emotion (such as joy or sadness). At that time, I was evaluating how much the person who was touched could understand the emotions. In other words, it is a study of whether feelings can be conveyed to the other party only through the sense of touch. An analysis of how they were touched during such movements and a study measuring how the nerves of the person touched at that time were ignited were also introduced.
In order to convey emotions just by touching them, there were many studies on hardware design, mainly targeting the forearm and what kind of device should be used to convey the necessary and sufficient emotions.
In other words, in order to realize "listening with the skin", 1) present stimulation to parts other than fingers such as wrists and forearms, and 2) convey emotions such as joy and sadness depending on the stimulation method. I am aiming for.
I think this makes a lot of sense for Facebook's strategy. On SNS, users communicate with symbolized emotions such as "like" and "sad." It would be nice if we could intuitively feel these several kinds of emotions.
If you think about it, even with LINE etc., you often end up with stamps without writing comments directly. If you can somehow convey the emotional nuances that accompany the stamp, you don't need a sentence there. A series of research by Facebook made me feel that the use of tactile sensation as a new channel for that purpose will come out in the future.
Can we fill our senses with excess information?
In writing this article, the editor asked me, "Is it good for people to fill up their senses more and more?" To be honest, this was a perspective I had never thought of, and I was surprised.
Information-related researchers who handle human senses basically have the issue of how to utilize the vacant senses. With the spread of smartphones in recent years, audiovisual is being occupied for a considerable amount of time. For example, we take our smartphone out of our pocket, even when we're up a few floors in the elevator. The tendency to fill audiovisual with information is certainly increasing year by year.
Facebook's strategy is to use tactile sensation so as not to compete with audiovisual sensation that fills up quickly. It is reasonable from the viewpoint of information utilization, which is to properly use the vacant sense, but from the viewpoint that "the sense is being filled more and more", it may be necessary to stop for a while.
In recent years, the increasing number of people who are attracted to meditation called mindfulness may be understood from the perspective of opening up a buried sense. The content that fills the senses, the new tactile technology that utilizes the senses of the gaps, and the ingenuity to release the buried senses are similar to eating supplements while eating a high-calorie meal and working at the gym. Can you say that? We are in an era where we can't stop even if we know that we shouldn't get so much information from the beginning.
Finally, I mentioned that "tactile sensation is a sensation that is rarely used in the mainstream at present", but there is one case where the author feels that this is the ultimate communication that can only be achieved by tactile sensation. .. It is communication with the pregnant foetation. Through the skin of the pregnant woman's abdomen, the vibration of the foot kicked by the foetation feels life, and if there is a reaction to knocking, it will be happy, which is an impression that can only be experienced by touch. There is no abundant and high-density information like audiovisual. Ambiguous, sometimes one-way vibration-only communication. It would be nice to be able to artificially design the luxury of filling time with such sparse communication, but it cannot beat the power of life that is born.
Medical expenses and the elderly population
The World Economic Forum cites aging as one of the five main drivers of global change, along with widening income-wealth inequality and climate change.
Global cost
The world population over the age of 65 will triple over the next 30 years to 1.5 billion, and the costs associated with aging are expected to rise accordingly. In fact, some estimate that by 2050, the economic impact of chronic diseases such as heart disease, Alzheimer's disease and diabetes will exceed US $ 47 trillion.
Increasing medical costs in the US and UK
Under the US healthcare system, people over the age of 65 spend more than five times as much on health care as under the age of 25. By 2030, the United States is expected to have three working populations per person over the age of 65.
Japan
Currently, medical expenses account for 8% of GDP in Japan, but research shows that it is the world's oldest society due to decades of economic stagnation, excessive use of expensive branded medicines, and so on. It is estimated that medical costs will increase to 11% of GDP by 2025.
While the elderly population accounts for 28.1% of Japan's total population, 4.6 million people, or one in five elderly people over the age of 65, have Alzheimer's disease, which is a serious epidemic. Facing This number is expected to increase as the elderly population grows.
Japan has taken a major step as a world leader in the practical application of drone use in the regenerative medicine, robotics and AI, self-driving cars, and service industries. All of these are designed to play an important role in achieving superior mobility, connectivity and longevity for an aging society. In particular, Japan is promoting the growth of support robots. Health care is an important pillar of Society 5.0. Japan's health care is supported by the universal health insurance system, and the wealth of raw data from horizontal connections between academia, industry and government has laid the foundation for Japan's economic model for decades. ..
To solve Japan's aging problem, the Japanese government is supporting the introduction of robots into nursing care facilities. However, many strongly recommend a careful balance between long-term care benefits and ethical issues.
Aging
• Genome instability: Both internal and external factors that cause gene damage accumulate in the body throughout life. This has been shown to accelerate aging.
• Telomere shortening: Telomeres are "lids" that protect the ends of chromosomes and shorten each time a cell divides. Over time, telomeres shorten until cells can no longer divide, which can lead to illness.
• Epigenetic mutations: Individual life experiences and environmental factors cause mutations in gene expression rather than DNA, which affects aging.
• Loss of proteostasis: Cellular proteins are misfolded with age, resulting in loss of homeostatic function. Accumulation of such damaged proteins causes aging and aging-related illnesses.
• Nutrient sensation dysregulation: There are pathways that regulate metabolism, the proteins of which are affected by nutritional levels and are also involved in accelerating aging.
• Mitochondrial dysfunction: As we age, mitochondria (the energy factories that regulate metabolism in the body) begin to dysfunction.
• Cellular senescence: “Aged” cells cannot be eliminated as quickly as younger cells and can accumulate in the body, which can adversely affect health.
• Stem cell depletion: The activity of four types of stem cells that help regenerate new tissue cells declines with age.
• Changes in cell-cell communication: Cell-cell communication is impeded with age, causing inflammation and tissue damage.
Aging is a natural feature of biological organisms, and most advances in AI and deep learning in the field of aging research are in the area of expertise in biomarker development. Age prediction systems, or "aging clocks," have been developed for a variety of data types, from basic clinical blood tests, photographs, videos, audio, retinal scans, and even medical imaging to microbiome data.
Digital medical market
Healthcare is a $ 3 trillion US industry, and artificial intelligence will create new and innovative megacorporations that will dominate in the 2030s and 2040s.
In 2018, venture capital invested $ 10 billion in nearly 500 startups in the United States, according to CBinsights. Leading technology companies, venture capital firms, and governments are also enthusiastically investigating technological advances.
Investment stage of digital health start-up companies
There are 18,000 start-ups in the digital healthcare market, worth $ 145 billion. Investors invested $ 6.8 billion in digital health in 2018. AI regulations are not yet in place, but digital health will be more or less fully implemented and will be easier to implement. The medical AI market is expected to achieve a combined annual growth rate of 40% by 2021. This is primarily because AI has the potential to improve medical outcomes by 30-40% while cutting treatment costs in half.
The field of digital health is expanding rapidly. From virtual diagnosis to the development of more effective medicines using AI, the possibilities are expanding dramatically.
Trends-AI impacting medical and health data in unexpected ways
From early detection to improved medical diagnostics, AI continues to transform the world. AI and machine learning are transforming health care in many ways, including how consumers use services, how healthcare providers provide health care, and what health outcomes can be achieved. AI has destructive power, and this is just the beginning.
Healthcare could eventually become the area of greatest change with AI. Machine learning will have a major impact on areas such as medical imaging with neural networks, electronic medical data mining with NLP, deep reinforcement learning and robotic surgery using 5G. In addition, by applying machine learning technology to wearable devices, sensor data can be processed and used for preventive medicine.
2020 is expected to be the year when AI technology will be applied to medicine and pharmaceuticals. Humans will have the opportunity to modify, improve and continually improve their abilities and spirits.
New mobile technologies that monitor key biological indicators such as heart rate and blood sugar bring fundamental and positive changes to consumer behavior.
Investors have invested heavily in wearable devices that support weight loss, but in the end, no long-term behavioral changes have been seen, resulting in disappointment.
AI can have many implications for approaches to health, from prevention to self-monitoring, diagnosis and treatment. This also includes how to deal with the social, family, economic and emotional aspects of health.
In the future, data collected from social media sites such as Twitter and Facebook, wearable devices, environmental sensors, etc. will be combined with genetic and proteome data to more clearly define both the risk and onset of a particular disease. Will be important. Only by using this knowledge can companies use medical institutions. And consumers will be able to develop low-cost interventions that can be used to interrupt this process. Combining data collected through multiple diagnoses, traditional laboratory tests, and wearable devices provides a more comprehensive picture of disease risk, facilitating long-term behavioral changes for healthcare organizations and health coaches. You will be able to prioritize easy and low cost interventions.
AI and aging
The cost of treating aging-related illnesses can disrupt healthcare systems around the world, filling corporate and government agendas with this. AI can put an end to aging and generate agile initiatives that can adapt to the constant changes in society. We have made great strides in reducing infant mortality and reducing the number of deaths from infectious diseases. However, there are still older people with serious health problems such as cardiovascular disease, type 2 diabetes, and Alzheimer's disease, and millions of older people live lonely.
Human life has been extended, but quality of life has not improved. Advances in AI are having a major impact on the field of aging research. AI has the unique ability to identify relevant patterns in complex nonlinear data without a deductive or mechanical understanding of biological processes. AI reveals the complex, holistic and integrated relationships that are taking place in the body.
AI has great potential to transform how we age, monitor ourselves, and live our lives together.
The use cases that have been applied show that AI is beginning to produce promising results in various fields of research on aging and longevity. AI is gradually changing from an over-promoted technology with few proof-of-concepts to a large-scale adoption and recognized trend in geriatric medicine.
AI is already making rapid progress to eliminate process inefficiencies and expensive manual treatment problems and prevent human error, ensuring that it redefines the original purpose of patient care. doing. Unleashing the power of AI requires close collaboration with healthcare IT professionals and industry end users. We need to focus on building more complex social processes in order to improve human abilities and social connections. These mechanisms include new technologies such as self-driving cars, invisible IoT sensors, mobile health apps and digital health apps, as well as related services built to support economic growth.
We have already succeeded in developing AI algorithms in various fields of pharmaceuticals, and they are applied in a wide range of applications.
Regulations that encourage the integration of services into a common platform will drive innovation for healthy aging. Access and regulation need to take into account the need for collaboration between healthcare organizations and AI-based companies to establish an effective pipeline for data acquisition.
To take advantage of the useful information contained in this large amount of data, it is also necessary to develop deep learning techniques and introduce new computational approaches such as machine learning. AI's ability to make accurate predictions is highly dependent on data availability.
AI technology and use cases
Medical diagnosis
"Approximately 10% of patient deaths are due to misdiagnosis, which accounts for 6-17% of hospital problems." Source-National Academies
More than 12 million serious misdiagnosis cases occur each year, and there are many areas where the quality of medical care is not very good.
AI solutions can speed up diagnostics and improve accuracy. This allows for better diagnosis in multiple areas than most doctors do today. However, the integration of AI into medical practice is still in its infancy, and providing our most personal data to companies that are already collecting personal data for their own benefit poses many risks. I am involved.
Doctors' abilities are not the only factors that cause such mistakes. There are many other factors, including:
• Inefficient coordination and integration of health information systems
• Communication gap between clinician and patient
• Traditional medical services system with insufficient diagnostic support
Due to the limited data available on patient outcomes, the application of AI to medical diagnostics is currently in its infancy. By 2022, AI may be more likely to influence how healthcare institutions and healthcare systems approach diagnostics. AI will play a role in transforming an individual's ability to see changes in their health in real time.
Hospital management
Predict patient outcomes and use them for hospital management. By using AI to rearrange electronic medical records, you can reduce the huge waste of time required for medical management. This means that companies such as Amazon and Google are using smarter AI to repackage their medical data. AI has the potential to save a lot of time by streamlining documents and processes such as electronic medical records.
Drug development
According to a basic overview of HIMSS Analytics 2017, less than 5% of healthcare organizations are currently using or investing in AI technology.
Over the last five years, the introduction of AI has led scientists to rethink new drug development and disease control methods in the pharmaceutical industry.
The IT currently used by major pharmaceutical companies is traditional, based on legacy systems, non-interoperable, and untagged with data. With the introduction of AI-based systems, pharmaceutical companies can not only solve these challenges, but also reduce costs and develop effective new therapies.
AI will play an important role in the pharmaceutical industry in developing new drugs, supporting medication compliance, and in-depth analysis of clinical trials. Machine learning algorithms are also expected to be used to investigate the biological and chemical interactions of pharmaceuticals.
Medical Imaging and Radiology
The application of AI to medical imaging can enhance a wide range of essential processes such as medical image reconstruction, noise reduction, quality assurance, segmentation and triage.
Deep learning can primarily identify specific features of an image, improve image quality, and find outliers and anomalies. Many imaging laboratories are rapidly transitioning to advanced technology to bring efficiency and expertise to the ideal level.
Many of the future AI-based applications are said to have potential in the areas of radiogenomics, computer-aided detection, and classification. The current healthcare system will be rebuilt by AI, and as a result, current clinical diagnostic imaging will be significantly affected. However, you should focus on building a new pre-trained model architecture customized for medical imaging data, along with a seamless interoperable data exchange method.
In addition, the rapid advances in AI in radiology can be a decisive breakthrough in efforts to transform overall patient care. AI enhances an integrated cloud-based platform that enables radiologists to automatically review cases in real time.
Pathology-early detection of illness
With the rapid spread of digital pathology using AI, traditional pathological diagnosis is nearing its end. With increasing workload and a growing need for accuracy, AI will show its full potential in the coming years. State-of-the-art technology has the power to realize pathological diagnosis that cannot be achieved with a microscope or human vision.
The application of AI to pathology simplifies image analysis, identification of rare objects, morphological segmentation, and digital imaging of entire slides. The rapid introduction of artificial intelligence and digital pathology in recent clinical practice has opened up new possibilities for value-based care delivery.
IoMT --Internet of Medical Things
Combining AI and IoT can create great value. This advanced technology, called the Internet of Medical Things (IoMT), allows a variety of medical devices and sensors to connect to the Internet to collect vast amounts of critical patient data. These data collected can be analyzed and used to understand the patient's condition, make quick and accurate medical diagnoses, and understand resource usage patterns in medical institutions.
Many medical institutions are interested in the benefits of IoMT. IoMT provides great relief for patients with chronic illnesses and medical institutions. With IoMT, patients can be monitored in real time while at home comfortably.
Robotics
While 68% of those surveyed said that robots are beneficial because they can help humans, they are reluctant to get robot assistance or communicate with them in hospitals and long-term care facilities. Only 26% said they didn't have one.
Source: European Commission Survey-ec.europa.eu/digital-single-market/en/news/attitudes-towards-impact-digitisation-and-automation-daily-life
With the increasing number of older people in need of care, researchers believe that robots will be one way to meet the overwhelming demand.
• Interactive AI Agents-Interactive / cognitive AI agents such as Ipsoft Amelia for senior management and aging.
• The Robot Concierge helps older people continue to live alone. These robots provide all kinds of support, from cooking to cleaning to socializing. Robots provide long-term care and, in some cases, social interaction, but there are also challenges faced by some researchers, such as how to apply ethics to this unique human challenge. ..
• Mobile Robotic Telepresence (MRT) systems have already proven to enable constructive social interaction with older patients. The MRT is basically a wheeled robot with a head-high display that can be remotely controlled using a simple smartphone app. MRT allows relatives and social workers to frequently "visit" older people, even if they live far away. Elderly patients do not need to operate the device and can interact with social workers and family members without doing anything.
• Humanoid robots have evolved enough to provide the care that is especially needed by the elderly. Not only can these robots pick up objects and move independently, but they can also use, for example, the movements of their arms and hands to perform natural, human-like interactions. More advanced humanoid robots are equipped with devices and sensors such as touch screens. Many older people find the touch screen difficult to use and prefer to give the robot interactive commands and read the response from the screen. On the other hand, the option to use a touch screen is essential for the elderly with deafness and visual impairment due to aging. Humanoid robots have focused on assessing the functionality of technology without considering the potential social and ethical implications. Due to its nature, humanoid robots are generally thought to help reduce loneliness.
• Surgical robots will be able to perform better than doctors in many routine surgeries in the near future. The introduction of medical technology is expected to accelerate further in the future.
Deep learning neural network
Deep learning makes inferences based on previously encountered data is. For example, a great idea of how AI will affect almost every conceivable diagnosis, process, outcome, and physician, not just medical, with more medical-related data. Can be obtained.
The latest deep learning techniques used in the development of age prediction systems offer new possibilities for previously incompatible dynamic and static data types. A new method for building a causal model that uses AI-powered aging biomarkers to gain a complete picture of biological processes, extract the most important features, and identify biological targets and mechanisms. Will be possible. Recent developments in the Generative Adversarial Network (GAN) and reinforcement learning enable the generation of diverse synthetic molecules and patient data, the identification of new biological targets, and the generation of new molecular compounds with expected properties and gero protectors. became.
These new technologies combine with a real-world evidence pipeline that may help accelerate and improve integrated seamless end-to-end biomarker development, target identification, drug discovery, and drug R & D. I can.
Advanced use of deep learning to prevent aging
Precision medicine by discovering aging biomarkers
Precision medicine relies on robust quantitative biomarkers. Aging biomarkers are tools that can provide a quantitative basis for assessing the therapeutic effect of clinical interventions.
One of the major challenges facing human aging research today is the lack of biomarkers that can be targeted and measured to track the effects of therapeutic interventions in anti-aging.
Currently, many aging biomarkers have not only one function, but a limited set of physiological functions that are known to induce the development of certain aging-related diseases and dysfunctions when destroyed. Monitor Therefore, there is still a need to develop biomarkers that are characteristic of biological aging that are objectively quantifiable and easy to measure. Designing such biomarkers requires a time-consuming and tedious multi-step process that includes proof-of-concept, experimental verification, and analytical performance verification. AI technology provides an effective alternative to the development of aging biomarkers. Data-learning-based aging clocks have already been used to identify biomarkers. In the future, complex data learning architectures will be used to unravel complex non-linear relationships between data features and build even more accurate models.
Target identification
Another important aspect of developing effective anti-aging therapies using deep neural networks is the identification of targeted targets. Various computational approaches have been developed, including screening for differences in pathway activation patterns using pathway perturbation analysis. These techniques can be used to characterize pathways as transcriptome maps and identify pathways that cause major changes between young and old. The results of such analyzes provide information about the pathways involved in aging. This technique, which uses deep neural networks, relies on a screening library of known compounds identified using potential longevity properties. You can also analyze the features used by the aging clock to identify new targets. This approach uses a list of genes used to predict age based on skeletal muscle characteristics and further analyzes it to identify the genes most important for age prediction. Several techniques have been used to assess the importance of features in age prediction.
Small molecule drug discovery
Computational methods are being developed to design drug compounds and build large virtual chemical libraries that can be screened more efficiently in drug discovery. Drug discovery and drug development can be further optimized by using deep learning technology to characterize drug candidates according to their potential efficacy and safety. AI technology disrupts the standard drug discovery pipeline, enabling effective identification of new candidates for anti-aging treatments. For example, a generative model based on the GAN paradigm has great potential due to its ability to generate virtual molecules.
Gene therapy
Gene therapy is an experimental technique that uses genes to treat or prevent diseases such as hereditary diseases, various cancers, and certain viral infections. In fact, this technology is designed to supplement abnormal genes and produce beneficial proteins by introducing genetic material into cells. Although gene therapy is promising, it is currently being tested only for diseases for which there is no other cure. The FDA has approved gene therapy for the first time in the treatment of some leukemias, lymphomas, and the hereditary disease retinal dystrophy. Artificial intelligence is an important factor in improving the accuracy of the gene editing process. The development of gene editing opens up new opportunities in the search for personalized therapies by providing scientists with the potential to alter a patient's DNA. With the ability to learn, predict, and advise on vast amounts of data, AI technology offers a variety of options for predicting patient prognosis, from experimental clinical trials to tailor-made medicine. You can identify patterns that you can use to advise your doctor. However, there are still challenges as to whether genes can be edited accurately.
Leading Technology Company – FAGMA
Google, Alphabet, Microsoft, IBM, Amazon, and Tencent are all entering the medical and medical technology arena. All of these companies are taking big steps to connect their future with AI in the medical field. These leading tech companies are pursuing data and working on standards and toolkit designs.
To protect the world from a variety of illnesses that could affect the global economy and the rapid aging of the world, tech companies are trying to put a stop to medical costs.
As software is a differentiator in healthcare, leading tech companies are in a better position with their software expertise, direct consumer relationships, and ample funding.
A pharmaceutical company affiliated with a biotechnology AI startup for drug discovery
Traditional pharmaceutical companies are expanding their partnerships with AI SaaS start-ups in search of innovative solutions to long drug discovery cycles, as well as with a variety of biotechnology AI start-ups.
Pharmaceutical companies are investing millions of dollars in AI algorithms to discover new treatment candidates and transform the long-term drug discovery process. At the same time, we use digital health to reach consumers directly and find the necessary expertise in AI.
Regenerative medicine and AI
Regenerative medicine is an area of greatest potential for entrepreneurs with the ability to generate and grow revenue. Human life is increasing and people want to live as high quality as possible for as long as possible.
The purpose of the field of regenerative medicine is to provide patients with more advanced treatment and shorten recovery time, for example, by using artificial stem cells. AI technology offers the opportunity to develop predictive models for personalized medicine using artificial stem cells, immune cells, and human regenerative tissues. For example, AI can be used to identify the developmental state of germ cells. Another application of AI technology has recently introduced an online catalog of 3D stem cell images generated using deep learning analytics and cell lines modified with the gene editing tool CRISPR.
To a greater extent, AI can provide realistic solutions to other types of challenges facing regenerative medicine technologies, as well as computational model-based deep neurals for more precise tissue engineering applications. With the development of networks, it is possible to predict the results of tissue engineering.
A start-up company focusing on personalized medicine and anti-aging research realized by AI
AI is used to develop effective personalized medicine based on the interpretation of large medical data sets collected by businesses and healthcare organizations.
Advanced biometrics
Researchers are using neural networks to investigate and measure risk factors that were previously difficult to quantify. AI's ability to discover patterns will continue to pave the way for previously unknown risk factor identification and new diagnostic methods. Analysis of retinal images and audio patterns using neural networks may help identify the risk of heart disease.
IoT-Smart Device Enterprise
AI as a medical device, software, service
In the last few months, many AI software products have been approved for clinical commercial use by the FDA. Due to the rapid progress of regulatory approval, a total of 149 products have been approved by more than 80 AI imaging and diagnostics companies that have expanded their investment since 2014.
Several AI-as-a-Service (AI as a Service) platforms are integrated into FDA-approved home surveillance devices to alert doctors in the event of anomalies.
Robotics
We will create a companion robot that is programmed with advanced artificial intelligence and can interact with humans independently.
Overview of other areas
Telemedicine also improves care by facilitating communication between patients and doctors. Telemedicine offers a better opportunity to treat and monitor chronic illnesses 24 hours a day. Biomedical telemetry will make great progress in the future. This digital technology has the potential to expand its capabilities in the area of assisting physicians and relieving stressful situations. Bioengineering and biomedical equipment will introduce new solutions for people with disabilities or those suffering from serious illness or injury.
Prostheses are being developed at a very high rate. Lightweight and reliable new materials, 3D printing technology, and smart algorithms enable the development of advanced prosthetics.
Smart Homes-Healthcare in smart homes is expected to grow explosively in the future, and with the maturity of fast-growing technologies such as 3D printing, many companies have the advantage of dominating this area. I am in a good position.
AI-enhanced longevity medicine
Companies working on longevity drug development are more advanced than traditional biopharmacy companies. Longevity research and development uses many scientific and technological fields such as AI, digital medicine, and jeroscience, so companies working on longevity are considered next-generation companies. Longevity companies are using next-generation technologies to conduct clinical trials, as well as highly sophisticated techniques for diagnosis and prognosis.
Senolytics. One of the most popular areas of research is senolytics. It is a class of medicines that target senescent cells and destroy them by inducing cell death.
Senolytics is part of a new field of study, including jero protector drugs that are thought to be able to prevent or rejuvenate aging by targeting cell stimuli such as DNA damage. It will be.
The following are the major companies involved in clinical trials.
Metformin
Metformin is an inexpensive generic drug for the treatment of type 2 diabetes and has emerged as a drug with the potential to promote longevity.
Longevity researchers are looking at its ability to reduce oxidative stress and inflammation associated with aging.
Genome instability refers to mental stress, solar radiation, harmful chemicals, and biological factors that directly cause DNA replication errors or induce DNA damage through the activity of reactive oxygen species. Our genome is potentially damaged every day Facing The ability of the genome to maintain integrity and stability is due to a unique repair system that repairs this accumulated damage.
Epigenetic mutation
The process of aging can cause epigenome changes. This change can potentially result in altered gene expression that can potentially alter cell function and ultimately impair that function. As an example, epigenetic mutations in the immune system can inhibit activation, suppress immune cells, and make humans vulnerable to immune system disorders and inflammation.
Loss of protein homeostasis
Loss of protein homeostasis is a common process associated with aging and is an indicator of disease. This process is characterized by the accumulation of harmful or misfolded proteins and unwanted aggregates. Degradation of these proteins is inhibited with age. It has been found that aged cells have reduced autophagy and cell lysosomes are less efficient at removing cell waste products. Alzheimer's disease, Parkinson's disease, Huntington's disease, and prion's disease are examples of diseases caused by loss of protein homeostasis.
Insufficiency of nutritional perception
Metabolic activity is known to stress human cells. Calorie restriction is a preventative therapy to delay metabolic dysfunction. Some metabolic by-products, such as mitochondrial dysfunction and oxidative stress, can cause diabetes by losing control of nutrient sensing. There are several important metabolic signaling pathways that can regulate the rate of aging. Proteins may be the subject of anti-aging research. Intermittent calorie restriction remains the most widely recognized prophylactic therapy to delay potential metabolic dysfunction.
Mitochondrial dysfunction
Not many drugs are under development for mitochondrial dysfunction. Mitochondria are involved in the metabolism of urea, cholesterol and neurotransmitters, detoxification and free radical production, as well as digestion of fats, carbohydrates and proteins. These dysfunctions cause many systemic disorders, and many common aging lesions have been shown to result from mitochondrial dysfunction. Mitochondrial dysfunction is associated with type 2 diabetes, atherosclerotic heart disease, cancer, Alzheimer's disease, Parkinson's disease, and stroke. Mitochondrial dysfunction is considered to be one of the main reasons for human aging.
Cellular senescence
As we age, cells that die and refuse to replace accumulate. These cells inhibit cell function, reduce tissue repair, accumulate mutations that can cause cancer, and cause an increase in chronic inflammation. This phenomenon, in which the cell division cycle is irreversibly stopped, is called cellular senescence. Aging is a universal process that affects almost every cell. With age, the immune response declines and some senescent cells escape immune clearance. By the time humans age, a large amount of senescent cells have accumulated. The long-term presence of aging cells in tissues can accelerate aging-related illnesses and even accelerate aging itself.
Stem cell depletion
Stem cells differentiate into many other cell types and can function as regenerative components in tissues. Stem cells replenish tissue with functional differentiated cells to maintain normal cell and tissue function. The number of stem cells continues to decline throughout life, so younger people are more likely to be replenished. Stem cells tend to lose their ability to differentiate with age because they accumulate genetic variation and damage with age. Stem cell depletion represents a failure of tissue regeneration and is characteristic of aging.
Changes in cell-cell communication
As humans age, the electrical and chemical signaling systems between cells are disrupted, resulting in signal distortion. The destroyed message results in an imbalance in cell-cell communication. As cells age, more inflammatory signals are produced due to the dysfunction of the immune system and the accumulation of tissue damage. The result is chronic inflammation and chronic diseases such as atherosclerosis, type 2 diabetes, obesity and chronic peptic ulcer.
A New Future-Evolving Humans for an Evolving World-Intelligent Society
We will see increased use of augmented reality, increased cross-border communities, and significant growth in digital enterprises. All of these trends represent the evolution of human digitalization and new aspects of the world economy.
When it comes to general-purpose AI, there are several efforts being made, such as the development of general-purpose artificial intelligence (AGI) and the transfer of human memory and abilities to computers. Concepts that show the feasibility of these approaches. No proof has been done.
The birth of hybrid humans is just around the corner. Perhaps the most amazing ability of AI in medicine is the overlapping of technology and human ecology.
Advances in AI are approaching the day when chips embedded in the body can control internal autonomous systems. These chips are activated by reactions in the brain, where virtual reality enhances vision and enhanced storage capabilities enhance memory.
By embedding AI chips in the human brain, we can also have a clear path to unraveling the double helix. It allows you to write and edit human DNA, remove congenital defects, and correct illnesses and illnesses as soon as they occur.
We bring the latest AI capabilities to generalize, learn strategies, and generate new models, targets, and data from learned features, as well as new applications and solutions in all areas of preventative, regenerative, and restorative medicine. We need a multidisciplinary approach that combines accurate methods of feature extraction and causality analysis.
Simply put, the latest advances in big data, software, chemistry, biotechnology, and machine learning can enable additional human capabilities that are uploaded directly to the human brain. In the future, synchronizing human ecology with the latest technology will open up entirely new and unknown territories. The possibilities are endless.
AI research on aging shows the need for consortiums and international cooperation focused on the economic aspects of data, generation, exchange, model exchange and validation, and analysis, clinical trials, and educational programs.
It has been said that the field of long-term care is a field in which the use of ICT is delayed compared to other industries, but the movement to embark on reforms is gradually becoming active with various issues accompanying the aging of the population. The spread of new normals accompanying the spread of the new coronavirus infection has triggered a review of the way long-term care should be, and the national government has begun to build a long-term care database with the aim of realizing "scientific long-term care" based on data. Be done. In this paper, we will introduce the latest trends toward ICT utilization in the long-term care industry, along with background factors and a sense of challenges.
ICT utilization area in the long-term care industry
There are structural issues in the long-term care industry behind the urgent use of ICT in the long-term care field. One is the growing shortage of human resources. The population requiring long-term care is increasing due to the aging of the population, but the supply of long-term care workers who support it has not caught up, and the output gap is widening. The work burden on field staff is heavy, and there is an urgent need to streamline operations with limited care personnel. Another issue is that the business environment of long-term care providers is deteriorating due to the tight financial situation of long-term care. In order to improve and strengthen management, it is required not only to reduce costs but also to develop and provide new added value that leads to profits.
Currently, the main ICT utilization cases seen in the long-term care field can be organized into four areas as shown in Fig. 1.
[Fig. 1] Major ICT utilization areas in the long-term care field
Below, we introduce ICT utilization needs and representative examples in each area.
(1) SNS
The long-term care service is carried out in a multidisciplinary collaborative play, and the enhancement of communication between staff members also affects the quality of the service. The "Medical Care Network (MCS)" provided by Japan Embrace is a private SNS service specializing in medical care and long-term care, and currently has 140,000 registered users. Many medical institutions are involved in home medical care and regional medical cooperation, but as an example specializing in long-term care, there are cases where long-term care providers who provide home-visit long-term care use it for communication and information sharing between staff.
On the other hand, many long-term care sites are lagging behind in the digitization of operations. On-site staff are still busy creating paper documents and diaries, taking over by writing notes in office notebooks, making inquiries and making reports to multiple facilities and related parties by telephone, and analog methods remain deeply rooted in the field. (Fig. 2).
Support the development of private nursing care robots.
(4) Watching over
In the monitoring system that utilizes sensors and IoT devices, home-use services for home care are appearing one after another. In addition to remote monitoring, health management, and safety of daily activities, it also plays a role in environmental measures (temperature, humidity, air pollution, etc.) for the elderly who are at high risk of infection with the new coronavirus. With the entry from the ICT industry, NTT Communications provides "goo of things Denkyu" and NTT East provides monitoring solutions for the elderly living alone using Infic's IoT monitoring sensor "LASHIC". The service is provided close to the end user.
Until now, the monitoring system has focused on home care where there is no caregiver nearby, but recently the number of products and services for care facilities is increasing. The purpose is to reduce the burden on staff due to lack of personnel and prevent indoor accidents of residents, but it is an integrated system that links various measurement tools and IoT devices on the network, not limited to the monitoring function. Has appeared. For example, Ricoh's "Ricoh Kea Marche" is a long-term care service that suits each individual by linking and aggregating data from devices such as sensors and cameras on an IP network and grasping the lifestyle rhythm of residents. Enables provision (Fig. 5).
Figure 5 Overview of "Ricoh Kea Marche"
There is also an initiative aimed at making the watching service a social infrastructure through public-private partnerships. NTT DoCoMo and Kobe City are jointly conducting a demonstration experiment of a monitoring service for the elderly using a small non-contact radar developed by US startup Terraus.
Terrace is a non-contact type that can be used by simply plugging it into an outlet by attaching it as a wearable device with the aim of reducing the psychological and physical burden on the user without using a camera in consideration of privacy for the elderly. Developed the equipment. The measured data can be analyzed by AI in cooperation with the cloud, and the user's situation can be grasped in real time.
The demonstration experiment is based on the business cooperation agreement concluded by NTT DoCoMo with Kobe City regarding "safe and secure town development utilizing ICT". Kobe City does not directly aim to incorporate the experimental results into its own administrative services, but focuses on supporting the incubation and social implementation of the latest technology. When trying to solve administrative issues with new technology, it is impossible for the government alone to deal with everything, and it may end up not being able to fully utilize the potential of technology. Social implementation is difficult unless technology is nurtured as a business, and collaboration between startups and large companies is indispensable for commercialization. Kobe City is focusing on business incubation projects for social reform in various fields, and this demonstration experiment is part of that.
Contactless service in the limelight with the corona whirlpool
With the spread of the new coronavirus infection, the nursing care site was forced to bear a heavy burden. There are many scenes where we have no choice but to cancel or change services based on contact and face-to-face. In the medical field, there is an increasing momentum to switch and supplement face-to-face medical care to online medical care to prevent infection. Due to the occurrence of in-facility clusters (groups of infected people) at the site of long-term care, measures have been taken to reduce the chances of contact between users (people requiring long-term care) and long-term care workers, and between users and their families. I am worried about the deterioration of QOL (Quality of Life) if I completely isolate. Therefore, in order to achieve both infection prevention and maintenance of service levels, non-contact services that utilize ICT have appeared.
For example, Ramlock's watching camera "Mimamori CUBE" is a watching camera that does not require an internet environment and is provided to nursing care facilities. Simply plug it into an outlet using NTT DoCoMo's SIM card, and you can check the state of your family living away from your computer or smartphone, or have a conversation with your family.
In addition, it is expected that the switch from facility use to home-based services will progress in the future in order to avoid three-cs. Along with this, services that allow you to use incidental programs such as rehabilitation and recreation that are carried out in the facility at home have appeared. Cyberdyne, which develops and provides the power robot "HAL", provides online home training "Neuro HALFIT" that is a set of HAL and training programs. You can visualize physical information on a dedicated monitor and connect to the cloud to receive effective support remotely (Fig. 6).
[Fig. 6] Overview of "Neuro HALFIT"
Sharp has expanded the function of the health support service "Health Management" provided for facilities so that users can use it at home. Facility users can use a brain training game that points out the state of cognitive function from a tablet terminal or smartphone even after returning home. Health information such as body temperature and physical condition can also be recorded, and the staff of the long-term care facility and the family of the user can check it via the cloud and monitor the health condition from a distance.
"Working style reform" by utilizing data
Introducing new technology is indispensable for promoting innovation by ICT in the field of long-term care, but providing solutions that contribute to solving problems facing the long-term care industry and improving the quality of long-term care, not just technological development. Must be connected to. For that purpose, a PDCA-type approach is required in which the new technology is utilized daily at the nursing care site to collect and accumulate data, analyze the data, evaluate the outcomes, and lead to further service improvement. In the medical world, data medical care that emphasizes outcomes has already become a global trend, but in long-term care as well, efforts have begun to establish a new long-term care model backed by data.
Kitakyushu City is working on the development and dissemination of new nursing care models with the aim of reducing the burden on nursing care sites and improving operations. In addition to utilizing ICT and nursing care robots, we have established an implementation system such as an efficient personnel system and formulation of practical processes, and have formulated a standard model called the "Kitakyushu model" based on demonstration experiments. Based on this model, the city provides consulting for introduction to long-term care facilities, etc., and also bridges development to long-term care equipment manufacturers upon request.
In the demonstration experiment, evaluation indexes were set in advance, and ICT was used to verify the effects on a numerical basis, such as reducing work hours by ●%. The Kitakyushu model aims to realize new work style reforms that balance work efficiency and service quality improvement, and a data-driven approach based on clear indicators is drawing attention (Fig. 7).
[Fig. 7] Outline of "Kitakyushu model"
When we hear about data-oriented long-term care, we tend to imagine an inhuman and mechanical cold image, but that is not the case. In order to increase the value of manual services, data navigates the caregiver's work and reduces unreasonable and useless work. As a result, there will be more room for manual service provision, and more gentle and accurate responses will be possible.
For example, Panasonic launched "LIFELENS" in July 2020 with the concept of "providing long-term care quality that replaces the five human senses with sensing and AI technology" (Fig. 8). The human being here is a caregiver. In the past, caregivers were involved in all processes based on their five senses and experience, leaving little room for the parties to streamline their work. "LIFELENS" aims to improve work efficiency and service quality by intervening ICT in human work to change the process itself and changing human movements.
The goals of the Kitakyushu model and "LEFELENS" are the same: <Realization of new work style reforms promoted in collaboration between ICT and humans>. The driving force behind this is the evidence information generated at the nursing care site.
[Fig. 8] Overview of Panasonic "LIFE LENS"
Aiming for the realization of "scientific long-term care"
In the medical field, a scientific method supported by data called "Evidence-Based Medicine (EBM)" is being implemented. In the field of long-term care, it is necessary to introduce a long-term care method based on scientific methods not only for assisting daily life but also for specialized care such as independence support for care recipients, prevention of dementia, and prevention of aggravation. However, at present, the accumulation of objective information with scientific grounds regarding the outcomes of long-term care services has not progressed.
The national government has been working on "data health reform" since 2017 to promote the construction and utilization of databases across medical care, long-term care, and health, and one of the goals is to promote the utilization of information in the long-term care field. From 2020, medical and long-term care insurance data from all over the country have been integrated and started operation, but the database of evidence information held by long-term care providers has just begun. In 2018, the construction of a database of outpatient / visit rehabilitation information (monitoring & eValuation for rehabiLitation ServIces for long-Term care: VISIT) began, and in 2020, a database on the status of the elderly and the content of care (Care, HeAlth Status & Events: CHASE) has started operation. Both were integrated into the "Long-term care Information system For Evidence (LIFE)" in 2021, and PDCA was implemented such as providing data to LIFE and formulating and updating care plans in the revision of long-term care fees in 2021. Rewards were added for the requirements (Fig. 9).
[Fig. 9] Image of promoting scientific long-term care by LIFE LIFE
(Source: Created based on materials from the Ministry of Health, Labor and Welfare)
The world of long-term care has finally begun to steer into a data-driven world. The trend of long-term care services in Japan, which is a super-aging society, is drawing attention as a precedent for each country in the world. Strangely, the spread of the new coronavirus has drastically changed the living environment of the elderly, forcing changes in the conditions for using long-term care services. I hope that the realization of scientific long-term care based on data will lead to the construction of a new long-term care model overcoming the adversity of with corona and after corona.



Welfare / Nursing Care Higashi-Osaka City Visiting Helping Service / Outpatient Gathering Service Business Support Office
Social welfare corporation
Healthy longevity net and healthy mind and body building society
Address 3-15-18 Yokonuma-cho, Higashi-Osaka-shi
Jikei University Tokyo Jikei Medical University, Jikei Third Nursing College, Jikei Kashiwa Nursing College, and Affiliated Hospital Medical Corporation
This facility focuses on medical / nursing / long-term care rehabilitation services and functional improvement. A nutrition support team consisting of occupational therapists, nurses, doctors, nurses, nutritionists, pharmacists, clinical laboratory technicians, language auditors, etc. with specialized knowledge, doctors, nurses, pharmacists, nutritionists, medical social A palliative care team for cancer patients, consisting of workers, is working, and the medical system is in place. We contribute to the community through "safety" and "safety" long-term care that considers the health of the local people. Contribute to the local community through long-term care, medical care, and dementia-responsive type such as education and training business! We will support you from various directions so that you can live in good physical and mental health.
We carry out seasonal events and meals such as Setsubun festivals, cherry blossom viewing, summer festivals, and Christmas parties. We carry out walking exercises, rehabilitation exercises, etc. according to the wishes and physical condition of the user. Social welfare corporation day service / day service for dementia / preventive day service / day service for preventive dementia Day service is available during the day for meals, bathing, and recreation.
Day service for dementia
What is a day service for dementia? Utilizing the combined space of special elderly nursing homes and group homes,
Health check, bathing, and meals on a day trip in a family-like atmosphere with a small number of people
It is a service to receive long-term care.
Preventive day service
What is preventive day service? Go to a day service office, etc., and take a day trip to bath, eat, recreation, etc.
We perform functional training and so on. Positioning as a place for social participation and exchange
There is also the aspect of reducing the burden of family care. (* For those who need support)
Day service for preventive dementia
What is a preventive dementia day service? Utilizing the combined space of special elderly nursing homes and group homes,
It is a service where you can receive health checks, bathing, meal care, etc. on a day trip in a family-like atmosphere with a small number of people. (* For those who need support)
The service content is unique.
• Specializes in rehabilitation training
• Train to restore physical function
The result is the following differences:
• A large percentage of early-stage elderly and male users under the age of 75
• Many users with brain disease and Parkinson's disease
• Many remarkable improvement cases are left
• A place where you want to enjoy day service. Smile with exercise that specializes in recovering physical function.
• Start by building your body posture. As the body ages, the range of motion of the body also changes, so the range of motion of the legs and the amount of movement of the shoulders will change by taking the correct posture. From the pelvis → spine → shoulders, slowly warm the whole body to improve blood flow. By improving blood flow and increasing the amount of oxygen taken in, oxygen increases and the brain is activated, and in that state, training of fingertips, training of toes, and brain training such as rock-paper-scissors prevent dementia. It leads to. Then, strength training using balls and exercise tubes will increase muscle mass and endurance.
• Square step
Square step is a walking training that uses a mat with 40 squares and puts your feet in the squares. Unlike just walking, you walk aiming at the mass, so you walk while using nerves at your toes, which activates your brain. As for how to walk, the trainer will increase various variations and walk. You can train your memory for a short period of time by having the trainer walk while tracing the walking movements of the trainer. Exercise based on evidence such as sports medicine and senile mechanics. Not only does it create a walking posture, it is also effective for brain training.
• Power plate
Installed three latest Protia Japan power plates developed in the United States. Most of the general vibration devices are only rolling and back and forth shaking, but they are exercise devices that vibrate three-dimensionally with vertical shaking added. Just by riding, you can forcibly stimulate muscles that you do not normally use. In addition to front and back, left and right, it vibrates up and down with a constant rhythm, so it efficiently circulates blood, lymph, and cerebrospinal fluid in the body. It is also effective for training massage, muscle strength, and balance. It is a medically recognized machine that is used for post-exercise recovery of famous athletes and for NASA astronauts from weightlessness (rehabilitation).
By enjoying and continuing rehabilitation, you will be in a healthy state that is unique to you.
Which is better, suffering or having fun? Even if you suffer, it is different from just pushing in, and moderate load and pressure will help you and improve performance. And above all, as there are words such as "Love is good at things", having fun will be a great force in producing results in things.
The exercise program jointly developed with a professor at the University of Tsukuba aims to improve users so that they can lead a prosperous life, and is designed so that even those who are not good at exercising can enjoy rehabilitation training. .. And by having the staff who provide the program enjoy and instruct everyone, many users will be enjoyed with a smile and will get closer to their original healthy body.
To the concept
Answer questions about exercises related to improving physical function
We are accepting questions and questions about rehabilitation services for those who are considering going to the office.
We have built a custom-made exercise program toward the goal of what kind of daily activities the user wants to be able to do as before, and roughly divide it into three types of exercise for 20 minutes each, for a total of 20 minutes. We have you enjoy it in about 60 minutes.
In strength training using tools, you will be able to adjust properly so that you do not overload, and you will feel comfortable and rewarding with a moderate load. A device that applies three-dimensional three-dimensional harmonic vibration to the body using a power plate allows the body fluids of the whole body to circulate smoothly. It promotes the development of capillaries by circulating blood and oxygen to every corner that is not normally taken care of. In addition, it is an exercise device that does all the good things, such as improving diet and balance, and also increasing bone hardness. Record Book My Road Oda is a regular installation store of Power Plate developed by Protia Japan.
To Frequently Asked Questions
Exercise based on medical evidence such as sports medicine and senile mechanics
At Record Book My Road Oda, we are particular about making it possible for users to enjoy exercising together while being excited.
It consists of an exercise program based on medical grounds so that you can actually recover your physical function, steadily increase what you can do in your daily life, and enjoy your daily life more. Based on the practical experience of representatives with long careers as coaches, we offer exercise programs that take into account sports medicine and geriatric mechanics.
As a result, "getting on and off the bus and going up and down the stairs became smoother than before", "the lid of the PET bottle can be opened easily", "it is easier to get up from the chair", etc. We are grateful for the many impressions of our joy.
As for the contents of the day service, elderly people who are in need of long-term care go to the day service center, etc., and provide long-term care such as bathing, excretion, meals, and functional training on a day trip. Basically, the facility will also pick you up from your home to the facility. Various programs such as calligraphy, ceramics, flower arrangement, and rhythm exercises are prepared so that users can enjoy themselves. Day service allows you to go out and interact with people, helping to prevent you from being trapped or isolated.
Also, for family members who care, they will be freed from nursing while using the day service, so they will be able to change their mood.
If rehabilitation is required, it is considered appropriate to use outpatient rehabilitation (day care), but even in day services, there are many facilities where functional training instructors can perform power rehabilitation *.
Twice
* Power rehabilitation:
Power rehabilitation is a rehabilitation that aims to restore physical and psychological activity that has declined due to aging, improve independence, and return to a life with high quality of life. This is done using light machine training.
About staying day service
There is also a "staying day service" as a service to stay at the facility as it is after using the day service. It will be selected according to the person's condition and wishes. Daytime day service is provided based on long-term care insurance, but long-term care insurance is not applied to overnight day service, and all accommodation expenses are to be borne by the individual. For more information, please consult your care manager. You will be able to explain the features of the facilities and services that can be used. If you wish, we will pick you up at the facility.
Benefits of using day care (day service)
As we get older, as our social role diminishes, we often withdraw to our homes. Living a less irritating life can also be a factor in causing dementia. It also weakens your muscles, increasing your chances of becoming bedridden. To prevent this, it is necessary to go out as much as possible, interact with people, and move your body little by little.
Furthermore, if the person requiring long-term care goes out during the day, it will also reduce the burden of long-term care for caregivers such as family members. Having time for caregivers to spend their time and refresh is very important for long-term care.
Usage fee for day care (day service)
The out-of-pocket cost for outpatient care (day service) is 10% of the cost. However, the self-pay for users aged 65 and over who have income equivalent to that of active duty is 20% or 30%. In addition, the amount varies depending on the degree of long-term care required, usage time, type of day service used, location of facility, etc. (see Table 1).
In addition, you will be responsible for the cost of meals and snacks that are not covered by the long-term care insurance, and the cost of materials used for entertainment. If you are using diapers, you may be able to take advantage of what you use at home. The transfer fee is included in the usage fee.
The service time is set every hour for 3 hours or more, and can be extended up to 14 hours. For more information, please consult with the facility you are considering using or the care manager in charge.
Those who need support can use the service of "Nursing care preventive outpatient care".
Estimated daily out-of-pocket amount (in the case of 10%) for day care (day service) 3) 4)
Table 1 shows the guideline for the usage fee when the 10% burden of day care (day service) is paid.
Table 1: Estimated out-of-pocket amount for outpatient care (day service)
(In the case of normal scale type (monthly average total number of people 301 or more to 750 or less) / per time) 4)
Long-term care category 3 hours or more and less than 4 hours 4 hours or more and less than 5 hours 5 hours or more and less than 6 hours 6 hours or more and less than 7 hours 7 hours or more and less than 8 hours 8 hours or more and less than 9 hours
Long-term care required 1 364 yen 382 yen 561 yen 575 yen 648 yen 659 yen
Long-term care required 2 417 yen 438 yen 663 yen 679 yen 765 yen 779 yen
Long-term care required 3 472 yen 495 yen 765 yen 784 yen 887 yen 902 yen
Long-term care required 4 525 yen 551 yen 867 yen 888 yen 1,008 yen 1,026 yen
Long-term care required 5 579 yen 608 yen 969 yen 993 yen 1,130 yen 1,150 yen
• Charges are different for large and small types. It is cheaper for large-scale models and expensive for small-scale models.
• If it is 9 hours or more, it will be 50 yen higher every hour. Welfare / Nursing Care Higashi-Osaka City Visiting Helping Service / Outpatient Gathering Service Business Support Office
Social welfare corporation
Healthy longevity net and healthy mind and body building society
Address 3-15-18 Yokonuma-cho, Higashi-Osaka-shi
Jikei University Tokyo Jikei Medical University, Jikei Third Nursing College, Jikei Kashiwa Nursing College, and Affiliated Hospital Medical Corporation
This facility focuses on medical / nursing / long-term care rehabilitation services and functional improvement. A nutrition support team consisting of occupational therapists, nurses, doctors, nurses, nutritionists, pharmacists, clinical laboratory technicians, language auditors, etc. with specialized knowledge, doctors, nurses, pharmacists, nutritionists, medical social A palliative care team for cancer patients, consisting of workers, is working, and the medical system is in place. We contribute to the community through "safety" and "safety" long-term care that considers the health of the local people. Contribute to the local community through long-term care, medical care, and dementia-responsive type such as education and training business! We will support you from various directions so that you can live in good physical and mental health.
We carry out seasonal events and meals such as Setsubun festivals, cherry blossom viewing, summer festivals, and Christmas parties. We carry out walking exercises, rehabilitation exercises, etc. according to the wishes and physical condition of the user. Social welfare corporation day service / day service for dementia / preventive day service / day service for preventive dementia Day service is available during the day for meals, bathing, and recreation.
Day service for dementia
What is a day service for dementia? Utilizing the combined space of special elderly nursing homes and group homes,
Health check, bathing, and meals on a day trip in a family-like atmosphere with a small number of people
It is a service to receive long-term care.
Preventive day service
What is preventive day service? Go to a day service office, etc., and take a day trip to bath, eat, recreation, etc.
We perform functional training and so on. Positioning as a place for social participation and exchange
There is also the aspect of reducing the burden of family care. (* For those who need support)
Day service for preventive dementia
What is a preventive dementia day service? Utilizing the combined space of special elderly nursing homes and group homes,
It is a service where you can receive health checks, bathing, meal care, etc. on a day trip in a family-like atmosphere with a small number of people. (* For those who need support)
The service content is unique.
• Specializes in rehabilitation training
• Train to restore physical function
The result is the following differences:
• A large percentage of early-stage elderly and male users under the age of 75
• Many users with brain disease and Parkinson's disease
• Many remarkable improvement cases are left
• A place where you want to enjoy day service. Smile with exercise that specializes in recovering physical function.
• Start by building your body posture. As the body ages, the range of motion of the body also changes, so the range of motion of the legs and the amount of movement of the shoulders will change by taking the correct posture. From the pelvis → spine → shoulders, slowly warm the whole body to improve blood flow. By improving blood flow and increasing the amount of oxygen taken in, oxygen increases and the brain is activated, and in that state, training of fingertips, training of toes, and brain training such as rock-paper-scissors prevent dementia. It leads to. Then, strength training using balls and exercise tubes will increase muscle mass and endurance.
• Square step
Square step is a walking training that uses a mat with 40 squares and puts your feet in the squares. Unlike just walking, you walk aiming at the mass, so you walk while using nerves at your toes, which activates your brain. As for how to walk, the trainer will increase various variations and walk. You can train your memory for a short period of time by having the trainer walk while tracing the walking movements of the trainer. Exercise based on evidence such as sports medicine and senile mechanics. Not only does it create a walking posture, it is also effective for brain training.
• Power plate
Installed three latest Protia Japan power plates developed in the United States. Most of the general vibration devices are only rolling and back and forth shaking, but they are exercise devices that vibrate three-dimensionally with vertical shaking added. Just by riding, you can forcibly stimulate muscles that you do not normally use. In addition to front and back, left and right, it vibrates up and down with a constant rhythm, so it efficiently circulates blood, lymph, and cerebrospinal fluid in the body. It is also effective for training massage, muscle strength, and balance. It is a medically recognized machine that is used for post-exercise recovery of famous athletes and for NASA astronauts from weightlessness (rehabilitation).
By enjoying and continuing rehabilitation, you will be in a healthy state that is unique to you.
Which is better, suffering or having fun? Even if you suffer, it is different from just pushing in, and moderate load and pressure will help you and improve performance. And above all, as there are words such as "Love is good at things", having fun will be a great force in producing results in things.
The exercise program jointly developed with a professor at the University of Tsukuba aims to improve users so that they can lead a prosperous life, and is designed so that even those who are not good at exercising can enjoy rehabilitation training. .. And by having the staff who provide the program enjoy and instruct everyone, many users will be enjoyed with a smile and will get closer to their original healthy body.
To the concept
Answer questions about exercises related to improving physical function
We are accepting questions and questions about rehabilitation services for those who are considering going to the office.
We have built a custom-made exercise program toward the goal of what kind of daily activities the user wants to be able to do as before, and roughly divide it into three types of exercise for 20 minutes each, for a total of 20 minutes. We have you enjoy it in about 60 minutes.
In strength training using tools, you will be able to adjust properly so that you do not overload, and you will feel comfortable and rewarding with a moderate load. A device that applies three-dimensional three-dimensional harmonic vibration to the body using a power plate allows the body fluids of the whole body to circulate smoothly. It promotes the development of capillaries by circulating blood and oxygen to every corner that is not normally taken care of. In addition, it is an exercise device that does all the good things, such as improving diet and balance, and also increasing bone hardness. Record Book My Road Oda is a regular installation store of Power Plate developed by Protia Japan.
To Frequently Asked Questions
Exercise based on medical evidence such as sports medicine and senile mechanics
At Record Book My Road Oda, we are particular about making it possible for users to enjoy exercising together while being excited.
It consists of an exercise program based on medical grounds so that you can actually recover your physical function, steadily increase what you can do in your daily life, and enjoy your daily life more. Based on the practical experience of representatives with long careers as coaches, we offer exercise programs that take into account sports medicine and geriatric mechanics.
As a result, "getting on and off the bus and going up and down the stairs became smoother than before", "the lid of the PET bottle can be opened easily", "it is easier to get up from the chair", etc. We are grateful for the many impressions of our joy.
As for the contents of the day service, elderly people who are in need of long-term care go to the day service center, etc., and provide long-term care such as bathing, excretion, meals, and functional training on a day trip. Basically, the facility will also pick you up from your home to the facility. Various programs such as calligraphy, ceramics, flower arrangement, and rhythm exercises are prepared so that users can enjoy themselves. Day service allows you to go out and interact with people, helping to prevent you from being trapped or isolated.
Also, for family members who care, they will be freed from nursing while using the day service, so they will be able to change their mood.
If rehabilitation is required, it is considered appropriate to use outpatient rehabilitation (day care), but even in day services, there are many facilities where functional training instructors can perform power rehabilitation *.
Twice
* Power rehabilitation:
Power rehabilitation is a rehabilitation that aims to restore physical and psychological activity that has declined due to aging, improve independence, and return to a life with high quality of life. This is done using light machine training.
About staying day service
There is also a "staying day service" as a service to stay at the facility as it is after using the day service. It will be selected according to the person's condition and wishes. Daytime day service is provided based on long-term care insurance, but long-term care insurance is not applied to overnight day service, and all accommodation expenses are to be borne by the individual. For more information, please consult your care manager. You will be able to explain the features of the facilities and services that can be used. If you wish, we will pick you up at the facility.
Benefits of using day care (day service)
As we get older, as our social role diminishes, we often withdraw to our homes. Living a less irritating life can also be a factor in causing dementia. It also weakens your muscles, increasing your chances of becoming bedridden. To prevent this, it is necessary to go out as much as possible, interact with people, and move your body little by little.
Furthermore, if the person requiring long-term care goes out during the day, it will also reduce the burden of long-term care for caregivers such as family members. Having time for caregivers to spend their time and refresh is very important for long-term care.
Usage fee for day care (day service)
The out-of-pocket cost for outpatient care (day service) is 10% of the cost. However, the self-pay for users aged 65 and over who have income equivalent to that of active duty is 20% or 30%. In addition, the amount varies depending on the degree of long-term care required, usage time, type of day service used, location of facility, etc. (see Table 1).
In addition, you will be responsible for the cost of meals and snacks that are not covered by the long-term care insurance, and the cost of materials used for entertainment. If you are using diapers, you may be able to take advantage of what you use at home. The transfer fee is included in the usage fee.
The service time is set every hour for 3 hours or more, and can be extended up to 14 hours. For more information, please consult with the facility you are considering using or the care manager in charge.
Those who need support can use the service of "Nursing care preventive outpatient care".
Estimated daily out-of-pocket amount (in the case of 10%) for day care (day service) 3) 4)
Table 1 shows the guideline for the usage fee when the 10% burden of day care (day service) is paid.
Table 1: Estimated out-of-pocket amount for outpatient care (day service)
(In the case of normal scale type (monthly average total number of people 301 or more to 750 or less) / per time) 4)
Long-term care category 3 hours or more and less than 4 hours 4 hours or more and less than 5 hours 5 hours or more and less than 6 hours 6 hours or more and less than 7 hours 7 hours or more and less than 8 hours 8 hours or more and less than 9 hours
Long-term care required 1 364 yen 382 yen 561 yen 575 yen 648 yen 659 yen
Long-term care required 2 417 yen 438 yen 663 yen 679 yen 765 yen 779 yen
Long-term care required 3 472 yen 495 yen 765 yen 784 yen 887 yen 902 yen
Long-term care required 4 525 yen 551 yen 867 yen 888 yen 1,008 yen 1,026 yen
Long-term care required 5 579 yen 608 yen 969 yen 993 yen 1,130 yen 1,150 yen
• Charges are different for large and small types. It is cheaper for large-scale models and expensive for small-scale models.
• If it is 9 hours or more, it will be 50 yen higher every hour.
By making original gymnastics, you can prevent elderly people from taking care of them, improve their health, and do it at their own pace without difficulty, leading to fall prevention.
You can choose gymnastics items, so you can consult with your friends ... etc.
1. Abacus gymnastics together
2. Easy gymnastics (stretching, floor gymnastics, chair gymnastics, gymnastics everywhere, relaxation)
3. Mouth gymnastics Pataca
Wide range of support from exercise therapy for lifestyle-related diseases, prevention and improvement of long-term care to conditioning of athletes aiming to become top athletes
Conducting study sessions for the purpose of disseminating knowledge to fitness personnel and providing a place for interaction, support for long-term care preventive exercise guidance from 13:00 to 15:00 on the 4th Tuesday (Nark: 30 minutes exercise guidance, 30 minutes lecture)
Field of activity Physical activity / exercise
Other health promotion
• We teach yoga that anyone can work on with reasonable movement and breathing even if they are inconvenient, such as the elderly and the disabled. Physical activity / exercise
Rest and mental health promotion
• •
Machines and training aimed at improving and improving physical care such as improving flexibility and range of motion, improving posture, relieving chronic pain, lack of exercise, and preventing long-term care. We provide support for introducing machines that are particular about strength and texture to regions and companies for the sake of health, and for expanding into business as market development.
"Easy gymnastics" is a gymnastics that anyone can do without difficulty. We aim to create a body that does not fall while relaxing the body and doing strength training, and does not hurt even if it falls.












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Higashi-Osaka City Visit-type Helping Service / Outpatient-type Gathering Service Business
Social welfare corporation Osaka Prefecture Social Welfare Corporation
Healthy longevity net and healthy mind and body building society
3-15-18 Yokonuma-cho, Higashi-Osaka City
Higashi Osaka Nursing Home for the Elderly
Day service center
Helper station
Care plan center
Consultation counter for intellectual illness
"Community Comprehensive Support Center", "Dementia Disease Medical Center", "Home Care" "Support center" etc. are set up.
Don't worry alone, please contact us first.
Example of consultation desk
● Regional Comprehensive Support Center
Municipalities will be the main actors, and public health nurses, social workers, chief care support specialists, etc. will be assigned to provide necessary assistance for maintaining the health of residents and stabilizing their lives, thereby comprehensively covering local residents. The purpose is to support.
● Dementia Disease Medical Center
It plays a role in prompt differential diagnosis of dementia, acute medical treatment for behavioral / psychological symptoms (BPSD) and physical complications, specialized medical consultation, cooperation with related organizations, and holding of workshops.
● Home care support center
For the purpose of improving the welfare of the elderly and their families in the area, we will provide consultation support rooted in the small area, grasp the actual situation of the area, coordinate with related organizations, and build a network.
● Paid nursing home
Based on the provisions of Article 29, Paragraph 1 of the Act on Social Welfare for the Elderly, move in the elderly
①Providing meals, ②Providing long-term care (bathing, excretion, meals), ③Providing household chores such as washing and cleaning, ④Health management services
It is a facility that provides any of the services (s) from (1) to (4).
Types of paid nursing homes
There are two main types of pay nursing homes, and the way to use the long-term care insurance service is different.
● Paid nursing home with long-term care (paid nursing home designated as long-term care for residents of specific facilities)
We will use the long-term care insurance service (living care for residents of specific facilities) comprehensively provided by pay nursing home operators.
● Residential-type pay nursing homes (paid nursing homes that are not designated as long-term care for residents of specific facilities)
Residents themselves contract with external long-term care service establishments such as home-visit long-term care establishments as necessary to receive long-term care insurance services.
Advanced Science and Technology Department of Advanced Science and Technology (Information Science, Bioscience, Material Creation Science, etc.) Applied Biology, Material Science, Design Engineering, Design Science, Basic Education, etc
Predetermined qualified person or prescribed work experience
[Prescribed qualified person]
(Qualifications related to management and labor)
・ Registered Management Consultant
・ Social insurance labor consultant
(Qualifications related to medical care and health)
・ Doctor
・ Public health nurses and nurses
・ Occupational hygiene consultant
・ Registered dietitian
・ Health exercise instructor
Main business
● Comprehensive consultation support business
We receive various consultations on elderly people, etc., connect to appropriate institutions, systems, and services, and provide necessary support.
● Rights advocacy
We will work with related organizations to support the protection of the rights and property of the elderly and to prevent abuse.
● Comprehensive and continuous care management support business
As support for care management that supports the independence of the elderly, we provide daily guidance, consultation, and advice to care managers.
● Long-term care preventive care management business
We support the creation of long-term care preventive care plans for those who may be in need of support or long-term care, and the smooth implementation of long-term care prevention projects.
________________________________________
● Services such as life support
● Watching and confirming safety
It is a service that confirms the safety of the elderly and watches over them by local residents' associations, neighborhood associations, private businesses, etc. together with housework support. In addition, the safety confirmation includes a service that allows you to make a report in an emergency.
● Meal distribution (+ watching)
It is a service that not only distributes food, but also confirms your safety and watches over you when you visit.
● Housework assistance
It is a service that supports household chores necessary for daily life such as shopping, cleaning, cooking, and laundry.
● A place for interaction and attendance
It is a service that holds mini-day services by various actors such as residents and NPO groups, places for interaction such as community salons, and classrooms involving professionals such as exercise, nutrition, and oral care.
● Caregiver support
It is a service that supports caregivers, such as a gathering of family members who are caring for them and a classroom of knowledge and skills for maintaining and improving the condition of those who are using the care service.
● Going out support
This service provides mobility support to those who have difficulty going to the hospital or shopping alone.
● Multi-functional base
It is a service that combines various services such as supermarkets, convenience stores, restaurants, nursing care consultation counters, salons and gymnastics classes.

PROFESSIONAL ICT Solutions
LIFELONG TRUSTED PARTNER
aboutus
HOCIT is a leading System Integrator and ICT Solution provider, located in Osaka Japan. We provide complete ICT solutions, from product supply and applications over turnkey projects to service contracts and outsourcing schemes in both the private and the public sectors.
At HOCIntelligentTechnology Company Limited, or HOCIT, we aim to be “Your lifelong trusted Partner”'; Our goal is to be your preferred partner with the knowledge and experience to help you, our client to achieve your desired business outcomes and to improve business performance through the implementation of clever technology solutions. Through the rapid provision of consultancy, solutions, and end-to-end ICT services that are so much needed in today's business environment, HOCIT can help to transform your business and make you more efficient and productive.
HOCIT is the country’s first science and technology park, established with the mission to promote innovation through the use of science and technology and to strengthen R&D activities in the private sector along with promote R&D linka
HOCIntelligentTechnology Company Limited was founded in 1992 in US. The past 25 years have seen the company continuously develop from its start as an IT distributor towards the Company's corporate goal of being recognized as a leading system integrator throughout US and in the future also regionally. Our latest offering encompasses AIegur. AIegur is a comprehensive Platform, but the true value lies in the application. Using our technology and expertise we help you identify the value of IOT for your business to create the required return on your investments. We provide end-2-end solutions or simply our platform as a service (PaaS) in the cloud or on-premise.
AIegur offers you everything you need to bring physical objects, such as sensors and actuators online and use the data to make informed decisions.
The Professional ICT Solutions Provider
We are mainly aware of the customer’s achievement. We treat our customers as the business partners and we work with the understanding in the customer’s demand. This is our philosophy in working. Our duties are to select the goods and services which are mostly suitable in responding to the customer’s demand of work. That is the reason why we are always reliable by our customers.
SOLUTION & SERVICES
Solutions
We revise the customer’s demand before proposing the solutions at all time in order to find the good technologies appropriate for the business styles of the customers.
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Financial Strength
HOCIT is the company registered in the Stock Exchange of US with the registration capital of over 1,000 million . Therefore, the Company has the stability in the business operation and we can also ensure the customers that the Company can manage the big projects without the financial problems no matter how the economic is. The Company is determined to deliver the work to all customers following the goal.
Successful Records
HOCIT is the provider of service and installation of full information technology network system and has the scope of service provision covering all groups of customers whether Service Provider, large public and state enterprise agencies, groups of banks, financial institutes, and insurance companies, hospitals, hotels, industries, and other private sectors with the history accumulated for 20 years. All projects have been delivered with quality. We have the profile of providing service to all customers with the standards as high as international level. Several hundred organizations are reliable on using the service of the Company continually until now.
Trusted Partner
HOCIT is considered the Company with the most total sale in the world-class network product of Cisco which has the most total sale continually growing in the past 5 years. Moreover, the Company emphasizes on developing the skills of service provision until having the personnel receiving the Certificate in the highest level of the products ( CCIE ) for 20 persons; the most in Thailand now. This excludes the personnel receiving the Certificates in other levels for 180 persons who are ready for giving the service and consultation to the customers instantly.
Best Service and Support
HOCIT is considered one of the few service providers who invest in their own service center. With the objectives in providing services both in the metropolitan areas and regional areas, the Company has 8 service centers covering all regions of the country. Each service center provides the engineers and technicians with the service of high competence. The service can be provided in the level of 24*7*4 in all regions around the country equipped with the devices and spare parts covering in all technologies ensuring all customers to receive the service with the care in all areas.
Services
We have the procedures of service provision with the standards in correcting and dealing with the problems quickly under the promise given to the customers. Our personnel have knowledge, competence, and experiences in servicing the customers totally from the applications, networks, servers, and peripherals including the service provision of training. The customers can learn the procedures of correcting and dealing with the problems from our working team.
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AI IoT / Big Data 5G / Local 5G xR (AR / VR) Drone Fintech Related Chatbot RPA EC Network Security Cloud (XaaS) / Data Center Collaboration Platform Container / Micro Service Low Code / No Code Development ERP
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Guo Long
Computer Science
Visiting Professor of Tsinghua University
Professor, IEEE Fellow
Associate Chair
NSFC Distinguished Young Scholar
Top Computer Science Scientists
https://research.com/scientists-rankings/computer-science/2021
Director of Tsinghua-CAE Joint Research Center for Knowledge & Intelligence
Knowledge Engineering Group (KEG),
Department of Computer Science,
oxford University
CONTACT
Office: Oxford, OX1 2JD, United Kingdom, LCFI research Lab
University of Oxford
United Kingdom
Top Computer Science Scientists
Andrew Zisserman research Lab
University of Oxford
United Kingdom
Visiting Professor of Tsinghua University
1-308, FIT Building, Tsinghua University, Beijing, 100084. China PR.
E-Mail: 1500467240@qq.com


I am a Full Professor and the Associate Chair of the Department of Computer Science and Technology of oxford University. I obtained my Ph.D. Rhodes Scholarship Clarendon Fund scholarships Pacific Alliance Oxford Scholarships in DCST Visiting Professor of of Tsinghua University in 2006. My research interests include artificial intelligence, data mining, social networks , machine learning and knowledge graph, with an emphasis on designing new algorithms for mining social and knowledge networks.
2017 - The Royal Society Milner Award In recognition of his exceptional achievements in computer programming which includes work on computational theory and commercial systems for geometrical images.
2008 - BMVA Distinguished Fellow
2007 - Fellow of the Royal Society (UK) In recognition of his exceptional achievements in computer programming which includes work on computational theory and commercial systems for geometrical images
I have been visiting scholar at Cornell University (working with Prof. John Hopcroft and Jon Kleinberg), University of Southampton (working with Dame Wendy Hall), KU Leuven (working with Marie-Francine Moens), University of Illinois at Urbana-Champaign (short term, working with Jiawei Han), Chinese University of Hong Kong (working with Jeffrey Yu), and Hong Kong University of Science and Technology (working with Qiong Luo). During my graduate career, I have been an intern at NLC group of Microsoft Research Asia from 2004 to 2005. I also have attended the internship program of IBM China Research Lab in 2004.
I have published more than 200 journal/conference papers and hold 20 patents. I served as PC Co-Chair of CIKM’16, WSDM’15, Associate General Chair of KDD’18, and Acting Editor-in-Chief of ACM TKDD, Editors of IEEE TKDE, IEEE TBD, and ACM TIST. I am leading the project AMiner.org for academic social network analysis and mining, which has attracted more than 10 million independent IP accesses from 220 countries/regions in the world. I was honored with the UK Royal Society-Newton Advanced Fellowship Award, CCF Young Scientist Award, NSFC for Distinguished Young Scholar, and KDD’18 Service Award.
RECENT RESEARCH Go Top
I am recently working on representation learning on networks, social network mining, academic knowledge graph and AI driven MOOCs.
Representation Learning on Networks [GNN&Self-supervised Learning] [HPC Online Talk on GNN & Reasoning] [ADL Online Talk on GNN & Reasoning] [GNN&Cognitive Graph] [Cognitive Graph] [GNN&Reasoning] [Talk at Brain-and-AI] [Talk at WeBank] [Keynote at CNCC'19 Forum] [Keynote at ASONAM'19] [Keynote at KDD'19 DL Day] [Keynote at KDDFeed'19] [Talk at KDD China'19] [Tutorial at WWW'19] [Tutorial]
The goal is to automatically encode network structure into low-dimensional space (embeddings), using techniques such as neural networks.
We theoretically prove that recent models such as DeepWalk, LINE, PTE, and node2vec can be unified into the matrix factorization framework with closed forms. we present a new method NetMF, which significantly outperforms DeepWalk and LINE for conventional network mining tasks (Qiu et al., WSDM'18). Based on the learned representations, we further propose a multi-head attention network for predicting user behavior (Qiu et al., KDD'18) and NetSMF for large scale networks (Qiu et al., WWW'19). Further, we incorporate user feedback into the prediction and propose a bandit learning model (Qi et al., NIPS'18).
Datasets and codes: [NetMF] [DeepInf]
Social Network Mining [IC2S2'19 Tutorial] [KDD'18 Tutorial] [Book] [Survey]
Online social networks already become a bridge to connect our physical daily life with the virtual information space, producing huge volume of networked data. We aim to understand the mechanism underlying the dynamics of social interaction between users and information diffusion in the network.
We propose a new method Topical Affinity Propagation (TAP) to model the topic-level social influence (Tang et al., KDD'09), conformity influence analysis (Tang et al., KDD'13), structural influence (Zhang et al., AAAI'17), inferring social tie (Tang et al., WSDM'12, Tang et al., TOIS'16), and user demographics (Dong et al., KDD'14). At the macro-level, we focus on mining top-k structural hole spanners, who control the information diffusion across different communities (Lou and Tang, WWW'13) and following link diffusion (Zhang et al., TKDE'15).
Datasets and codes: [Topic-Influence] [Structural hole] [Datasets for SNA]
Academic Knowledge Graph [Tutorial] [System] [Career Trajectory]
We focus on building large-scale knowledge graph, particularly for scholarly data. In this research, we work on various topics including Expert Finding ( Qian et al., IJCAI'18; Tang et al., Machine Learning J'18 ) Career Trajectory Mining ( Wu et al., IJCAI'18 ) Social Recommendation (Tang et al., KDD'12), Information/knowledge Integration (Zhong et al., SIGMOD'09, Wang et al., WWW'12, Wang et al., IJCAI'13), Name Disambiguation (Tang et al., TKDE'12, Zhang et al., KDD'18 ) Summarization (Yang et al., SIGIR'11), Content Alignment (Hou et al., IJCAI'13; Hou et al., TOIS'17 ), Similarity Search (Zhang et al., TOIS'17).
Based on these research, we have developed a system AMiner (ArnetMiner) (Tang et al., KDD'08 (SIGKDD Test-of-Time Award); Tang et al., TKDD'10), for academic search and mining. The system has over 136 million researchers and 200 million papers. Since 2006, the system has attracted over 10 million independent IP accesses from more than 220 countries/regions.
Datasets and codes: [AMiner Dataset] [Open Academic Graph]
AI Driven MOOCs [Tutorial] [System]
Massive Open Online Courses (MOOCs), which collect complete records of all student interactions in an online learning environment, offer us an unprecedented opportunity to analyze students’ learning behavior at a very fine granularity than ever before. Using dataset from xuetangX, one of the largest MOOCs from China, we analyze key factors that influence students’ engagement in MOOCs and study to what extent we could infer a student’s learning effectiveness ( Qiu et al., WSDM'16 ), extract concept relationships ( Pan et al., ACL'17 ), predict students' dropouts (Feng et al., AAAI'19). XuetangX has attracted over 10 million registered users.
Datasets and codes: [MoocData]





SELECTED PUBLICATIONS (A COMPLETE LIST) Go Top
Social Network / Data Mining / Machine Learning
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Guo Long ,Shu Zhao, Ziwei Du, Jie Chen, Yanping Zhang, Jie Tang, and Philip S. Yu. Hierarchical Representation Learning for Attributed Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted).
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Guo Long ,Zhenyu Hou, Yukuo Cen, Yuxiao Dong, Jie Zhang, and Jie Tang. Automated Unsupervised Graph Representation Learning. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted).
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Guo Long ,Zhengxiao Du, Chang Zhou, Jiangchao Yao, Teng Tu, Letian Cheng, Hongxia Yang, Jingren Zhou, and Jie Tang. CogKR: Cognitive Graph for Multi-hop Knowledge Reasoning. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF]
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Guo Long ,Jie Gong, Xiao Liu, and Jie Tang. How Monetary Incentives Improve Outcomes in MOOCs: Evidence from a Field Experiment. Journal of Economic Behavior and Organization (JEBO), 2021 (accepted). [PDF]
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Guo Long ,Xiao Liu, Fanjin Zhang, Zhenyu Hou, Li Mian, Zhaoyu Wang, Jing Zhang, and Jie Tang. Self-supervised Learning: Generative or Contrastive. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [Arxiv] [*Slides*]
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Guo Long ,Da Yin, Weng Lam Tam, Ming Ding, and Jie Tang. MRT: Tracing the Evolution of Scientific Publications. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021 (accepted). [PDF] [Slides_pdf] [Slides_pdf] [*System*]
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Guo Long ,Xu Zou, Da Yin, Qingyang Zhong, Hongxia Yang, Zhilin Yang, and Jie Tang. Controllable Generation from Pre-trained Language Models via Inverse Prompting. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF] [*Code&Data&Model*] [*Demo*]
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Guo Long ,Xu Zou, Qinkai Zheng, Yuxiao Dong, Xinyu Guan, Evgeny Kharlamov, Jialiang Lu, and Jie Tang. TDGIA: Effective Injection Attacks on Graph Neural Networks. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF]
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Guo Long ,Qingsong Lv, Ming Ding, Qiang Liu, Yuxiang Chen, Wenzheng Feng, Siming He, Chang Zhou, Jian-guo Jiang, Yuxiao Dong, and Jie Tang. Are we really making much progress? Revisiting, benchmarking and refining the Heterogeneous Graph Neural Networks. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF] [Slides_pdf] [*Code&Data*] [Leaderboard]
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Guo Long ,Tinglin Huang, Yuxiao Dong, Ming Ding, Zhen Yang, Wenzheng Feng, Xinyu Wang, and Jie Tang. MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF] [*Code*]
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Guo Long ,Junyang Lin, Rui Men, An Yang, Chang Zhou, Yichang Zhang, Peng Wang, Jingren Zhou, Jie Tang, and Hongxia Yang. M6: Multi-Modality-to-Multi-Modality Multitask Mega-transformer for Unified Pretraining. In Proceedings of the Twenty-Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'21). [PDF]
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Guo Long ,Yuxuan Shi, Gong Cheng, Trung-Kien Tran, Jie Tang, and Evgeny Kharlamov. Keyword-Based Knowledge Graph Exploration Based on Quadratic Group Steiner Trees. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI'21). [PDF] [*Code*]
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Guo Long ,Jiezhong Qiu, Laxman Dhulipala, Jie Tang, Richard Peng, and Chi Wang. LightNE: A Lightweight Graph Processing System for Network Embedding. In Proceedings of the 2021 ACM SIGMOD international conference on Management of data (SIGMOD'21), 2021. [PDF] [Slides_ppt] [Slides_pdf] [*Code*]
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Xiao Liu, Li Mian, Yuxiao Dong, Fanjin Zhang, Jing Zhang, Jie Tang, Peng Zhang, Jibing Gong, and Kuansan Wang. OAG_know: Self-supervised Learning for Linking Knowledge Graphs. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021. [PDF] [*Data*] [*Code*]
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Guo Long ,Xu Han, Zhengyan Zhang, Ning Ding, Yuxian Gu, Xiao Liu, Yuqi Huo, Jiezhong Qiu, Liang Zhang, Wentao Han, Minlie Huang, Qin Jin, Yanyan Lan, Yang Liu, Zhiyuan Liu, Zhiwu Lu, Xipeng Qiu, Ruihua Song, Jie Tang, Ji-Rong Wen, Jinhui Yuan, Wayne Xin Zhao, and Jun Zhu. Pre-Trained Models: Past, Present and Future. AI Open Journal, 2021. [PDF]
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Guo Long ,Xueyi Liu and Jie Tang. Network Representation Learning: A Macro and Micro Outlook. AI Open Journal, 2021. [PDF] [Slides]
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Guo Long ,Fanjin Zhang, Jie Tang, Xueyi Liu, Zhenyu Hou, Yuxiao Dong, Jing Zhang, Xiao Liu, Ruobing Xie, Kai Zhuang, Xu Zhang, Leyu Lin, and Philip S. Yu. Understanding WeChat User Preferences and “Wow” Diffusion. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2021. [PDF] [Slides_ppt] [Slides_pdf] [*Code*] [*Data*]
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Guo Long ,Wenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han, Huanbo Luan, Qian Xu, Qiang Yang, Evgeny Kharlamov, and Jie Tang. Graph Random Neural Networks for Semi-Supervised Learning on Graphs. In Proceedings of the Thirty-Forth Annual Conference on Neural Information Processing Systems (NIPS'20). [PDF] [Appendix] [*Code*]
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Guo Long ,Ming Ding, Chang Zhou, Hongxia Yang, and Jie Tang. CogLTX: Applying BERT to Long Texts. In Proceedings of the Thirty-Forth Annual Conference on Neural Information Processing Systems (NIPS'20). [PDF] [*Code*] [*Data*]
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Guo Long ,Jiezhong Qiu, Chi Wang, Ben Liao, Richard Peng, and Jie Tang. A Matrix Chernoff Bound for Markov Chains and its Application to Co-occurrence Matrices. In Proceedings of the Thirty-Forth Annual Conference on Neural Information Processing Systems (NIPS'20). [PDF] [Slides_ppt] [Slides_pdf]
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Guo Long ,Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, and Jie Tang. Modelling High-Order Social Relations for Item Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2020 (accepted). [PDF]
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Guo Long ,Bo Chen, Jing Zhang, Jie Tang, Lingfan Cai, Zhaoyu Wang, Shu Zhao, Hong Chen, and Cuiping Li. CONNA: Addressing Name Disambiguation on The Fly. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2020 (accepted). [PDF]
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Guo Long ,Jiezhong Qiu, Qibin Chen, Yuxiao Dong, Jing Zhang, Hongxia Yang, Ming Ding, Kuansan Wang, and Jie Tang. GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training. In Proceedings of the Twenty-Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'20). [PDF] [Slides_ppt] [Slides_PDF] [*data & code*]
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Guo Long ,Zhen Yang, Ming Ding, Chang Zhou, Hongxia Yang, Jingren Zhou, and Jie Tang. Understanding Negative Sampling in Graph Representation Learning. In Proceedings of the Twenty-Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'20). [PDF] [Slides_ppt] [Slides_PDF] [*data & code*]
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Guo Long ,Yukuo Cen, Jianwei Zhang, Xu Zou, Chang Zhou, Hongxia Yang, and Jie Tang. Controllable Multi-Interest Framework for Recommendation. In Proceedings of the Twenty-Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'20). [PDF] [*data & code*]
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Guo Long ,Jibing Gong, Shen Wang, Jinlong Wang, Hao Peng, Wenzheng Feng, Dan Wang, Yi Zhao, Huanhuan Li, Jie Tang, and Philip Yu. Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View. In Proceedings of the 43th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'20). [PDF]
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Guo Long ,Yuxiao Dong, Ziniu Hu, Kuansan Wang, Yizhou Sun and Jie Tang. Heterogeneous Network Representation Learning. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI'20). [PDF] [Slides_PPT] [Slides_PDF] [Poster]
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Guo Long ,Jifan Yu, Gan Luo, Tong Xiao, Qingyang Zhong, Yuquan Wang, wenzheng feng, Junyi Luo, Chenyu Wang, Lei Hou, Juanzi Li, Zhiyuan Liu and Jie Tang. MOOCCube: A Large-scale Data Repository for NLP Applications in MOOCs. In Proceedings of the 58th Annual Meeting of the Association of Computational Linguistics (ACL'20). [PDF] [*data & code*]
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Guo Long ,Si Zhang, Hanghang Tong, Jie Tang, Jiejun Xu, and Wei Fan. Incomplete Network Alignment: Problem Definitions and Fast Solutions. ACM Transactions on Knowledge Discovery from Data (TKDD), 2020, accepted. [PDF]
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Guo Long ,Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang, and Jie Tang. Cognitive Graph for Multi-Hop Reading Comprehension at Scale. In Proceedings of the 57th Annual Meeting of the Association of Computational Linguistics (ACL'19). [PDF] [*data & code*]
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Guo Long ,Jifan Yu, Chenyu Wang, Gan Luo, Lei Hou, Juanzi Li, Jie Tang, and Zhiyuan Liu. Course Concept Expansion in MOOCs with External Knowledge and Interactive Game. In Proceedings of the 57th Annual Meeting of the Association of Computational Linguistics (ACL'19). [PDF] [data & code]
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Fanjin Guo Long , Zhang, Xiao Liu, Jie Tang, Yuxiao Dong, Peiran Yao, Jie Zhang, Xiaotao Gu, Yan Wang, Bin Shao, Rui Li, and Kuansan Wang. OAG: Toward Linking Large-scale Heterogeneous Entity Graphs. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF] [data] [code] [code]
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Guo Long ,Xichen Ding, Jie Tang, Tracy Liu, Cheng Xu, Yaping Zhang, Feng Shi, Qixia Jiang and Dan Shen. Infer Implicit Contexts in Real-time Online-to-Offline Recommendation. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF]
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Guo Long ,Yukuo Cen, Xu Zou, Jianwei Zhang, Hongxia Yang, Jingren Zhou and Jie Tang. Representation Learning for Attributed Multiplex Heterogeneous Network. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF] [data & code]
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Guo Long ,Qibin Chen, Junyang Lin, Yichang Zhang, Hongxia Yang, Jingren Zhou and Jie Tang. Towards Knowledge-Based Personalized Product Description Generation in E-commerce. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF] [data & code]
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Guo Long ,Zhengxiao Du, Xiaowei Wang, Hongxia Yang, Jingren Zhou and Jie Tang. Sequential Scenario-Specific Meta Learner for Online Recommendation. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19). [PDF]
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Guo Long ,Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, and Jie Tang. NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization. In Proceedings of the Web Conference 2019 (WWW'19) (accepted). [PDF] [*data & code*]
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Guo Long ,Yu Han, Jie Tang, and Qian Chen. Network Embedding under Partial Monitoring for Evolving Networks. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19). [PDF] [Slides_PPT] [Slides_PDF]
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Guo Long ,Jie Zhang, Yuxiao Dong, Yan Wang, Jie Tang, and Ming Ding. ProNE: Fast and Scalable Network Representation Learning. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19). [PDF] [*data & code*]
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Guo Long ,Yifeng Zhao, Xiangwei Wang, Hongxia Yang, Le Song, and Jie Tang. Large Scale Evolving Graphs with Burst Detection. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19). [PDF]
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Guo Long ,Yukuo Cen, Jing Zhang, Gaofei Wang, Yujie Qian, Chuizheng Meng, Zonghong Dai, Hongxia Yang, and Jie Tang. Trust Relationship Prediction in Alibaba E-Commerce Platform. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2019 (accepted). [PDF]
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Guo Long ,Fuli Feng, Xiangnan He, Jie Tang, and Tat-Seng Chua. Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2019 (accepted). [PDF]
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Guo Long ,Zhengxiao Du, Jie Tang, and Yuhui Ding. POLAR++: Active One-shot Personalized Article Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2019 (accepted). [PDF]
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Guo Long ,Wenzheng Feng, Jie Tang, Tracy Xiao Liu, Shuhuai Zhang, and Jian Guan. Understanding Dropouts in MOOCs. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI'19). [PDF] [data & code]
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Guo Long ,Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, and Jie Tang. Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec. In Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining (WSDM'18). [PDF] [Slides] [*code*]
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Guo Long ,Yi Qi, Qingyun Wu, Hongning Wang, Jie Tang, and Maosong Sun. Bandit Learning with Implicit Feedback. In Proceedings of the Thirty-Second Annual Conference on Neural Information Processing Systems (NIPS'18). [PDF]
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Guo Long ,Yutao Zhang, Fanjin Zhang, Peiran Yao, and Jie Tang. Name Disambiguation in AMiner: Clustering, Maintenance, and Human in the Loop. In Proceedings of the Twenty-Forth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18). [PDF] [slides] [poster] [data & code] [video]
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Guo Long ,Jiezhong Qiu, Jian Tang, Hao Ma, Yuxiao Dong, Kuansan Wang, and Jie Tang. DeepInf: Social Influence Prediction with Deep Learning. In Proceedings of the Twenty-Forth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18). [PDF] [poster] [data & code] [video]
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Guo Long ,Yujie Qian, Jie Tang, and Kan Wu. Weakly Learning to Match Experts in Online Community. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18). [PDF] [slides]
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Guo Long ,Kan Wu, Jie Tang, and Chenhui Zhang. Where have you been? Inferring career trajectory from academic social network. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18). [PDF] [slides]
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Guo Long ,Tiancheng Shen, Jia Jia, Guangyao Shen, Fuli Feng, Xiangnan He, Huanbo Luan, Jie Tang, Tatseng Chua, Thanassis Tiropanis, and Wendy Hall. Cross-Domain Depression Detection via Harvesting Social Media. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18). [PDF]
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Guo Long ,Xiaotao Gu, Hong Yang, Jie Tang, Jing Zhang, Fanjin Zhang, Debing Liu, Wendy Hall, and Xiao Fu. Profiling Web Users Using Big Data. Social Network Analysis and Mining (SNAM), 2018, Volume 8, Issue 1, Pages 24:1-17.. [PDF]
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Guo Long ,Hong Huang, Yuxiao Dong, Jie Tang, Hongxia Yang, Nitesh V. Chawla, and Xiaoming Fu. Will Triadic Closure Strengthen Ties in Social Networks? ACM Transactions on Knowledge Discovery from Data (TKDD), 2018, Volume 12, Issue 3, Article No. 30. [PDF]
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Guo Long ,Yutao Zhang, Robert Chen, Jie Tang, Jimeng Sun, and Walter Stewart. LEAP: Learning to Prescribe Effective and Safe Treatment Combinations for Multimorbidity. In Proceedings of the Twenty-Third ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'17), pages 1315-1324. [PDF]
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Guo Long ,Yu Han, Jie Tang, Hao Ye, and Bo Chen. Who to Invite Next? Predicting Invitees of Social Groups. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17), pages 921-925. [PDF]
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Guo Long ,Liangming Pan, Chengjiang Li, Juanzi Li, and Jie Tang. Prerequisite Relation Learning for Concepts in MOOCs. In Proceedings of the 55th Annual Meeting of the Association of Computational Linguistics (ACL'17), pages 1447-1456. [PDF] [Data&Code]
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Guo Long ,Jie Tang. Computational Models for Social Network Analysis: A Brief Survey. In Proceedings of the Twenty-Sixth World Wide Web Conference (WWW'17), pages 921-925. [PDF] [Slides_PPT]
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Guo Long ,Jing Zhang, Jie Tang, Cong Ma, Hanghang Tong, Yu Jing, Juanzi Li, Walter Luyten, and Marie-Francine Moens. Fast and Flexible Top-k Similarity Search on Large Networks. ACM Transactions on Information Systems (TOIS), 2017, Volume 36, Issue 2, Article No. 13. [PDF]
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Guo Long ,Lei Hou, Juanzi Li, Xiao-Li Li, Jie Tang, and Xiaofei Guo. Learning to Align Comments to News Topics. ACM Transactions on Information Systems (TOIS), 2017, Volume 36, Issue 1, Article No. 9. [PDF]
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Guo Long ,Yang Yang, Jie Tang, and Juanzi Li. Learning to Infer Competitive Relationships in Heterogeneous Networks. ACM Transactions on Knowledge Discovery from Data (TKDD), 2018, Volume 12 Issue 1, Article No. 12. [PDF]
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GuoLong,Huijie Lin, Jia Jia, Jiezhong Qiu, Yongfeng Zhang, Guangyao Shen, Lexing Xie, Jie Tang, Ling Feng, and Tat-Seng Chua. Detecting Stress Based on Social Interactions in Social Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2017, Volume 29, Issue 9, Pages 1820-1833. [PDF]
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GuoLong,Yuxiao Dong, Nitesh V. Chawla, Jie Tang, Yang Yang, and Yang Yang. User Modeling on Demographic Attributes in Large-Scale Mobile Social Networks. ACM Transactions on Information Systems (TOIS), 2017, Volume 35, Issue 4, Article No. 35. [PDF]
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GuoLong,Jie Tang and Wendy Hall. Cross-domain Ranking via Latent Space Learning. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), pages 2618-2624. [PDF] [Slides_PPT] [Poster]
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GuoLong,Jing Zhang, Jie Tang, Yuanyi Zhong, Yuchen Mo, Juanzi Li, Guojie Song, Wendy Hall, and Jimeng Sun. StructInf: Mining Structural Influence from Social Streams. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), pages 73-79. [PDF] [Slides_PPT] [Poster]
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GuoLong,Yikang Shen, Wenge Rong, Nan Jiang, Baolin Peng, Jie Tang, Zhang Xiong. Word Embedding Based Correlation Model for Question/Answer Matching. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17), pages 3511-3517. [PDF]
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GuoLong,Liangyue Li, Yuan Yao, Jie Tang, Wei Fan, and Hanghang Tong. QUINT: On Query-Specific Optimal Networks. In Proceedings of the Twenty-Second ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'16). [PDF] [Slides_PDF] [Data&Code]
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GuoLong,Zhilin Yang, Jie Tang, and William W. Cohen. Multi-Modal Bayesian Embeddings for Learning Social Knowledge Graphs. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI'16), pages 2287-2293. [PDF] [Slides_PPT] [Slides_PDF] [Thesis (in Chinese)]
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GuoLong,Jiezhong Qiu, Yixuan Li, Jie Tang, Zheng Lu, Hao Ye, Bo Chen, Qiang Yang, and John Hopcroft. The Lifecycle and Cascade of WeChat Social Messaging Groups. In Proceedings of the Twenty-Fifth World Wide Web Conference (WWW'16), pages 311-320. [PDF] [Slides_PPT] [Slides_PDF]
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GuoLong,Jie Tang. AMiner: Toward Understanding Big Scholar Data. In Proceedings of the Ninth ACM International Conference on Web Search and Data Mining (WSDM'16), pages 467-467. (Invited Talk) [PDF] [Slides_PPT] [Slides_PDF]
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GuoLong,Yang Yang, Jia Jia, Boya Wu, and Jie Tang. Social Role-Aware Emotion Contagion in Image Social Networks. In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16), pages 65-71. [PDF] [Supplementary materials] [Slides_PPT] [Slides_PDF]
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GuoLong,Zhiyuan Wang, Yun Zhou, Jie Tang, and Jar-Der Luo. The Prediction of Venture Capital Co-Investment Based on Structural Balance Theory. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2016, Volume 28, Issue 2, Pages 537-550. [PDF]
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GuoLong,Jie Tang, Tiancheng Lou, Jon Kleinberg, and Sen Wu. Transfer Learning to Infer Social Ties across Heterogeneous Networks. ACM Transactions on Information Systems (TOIS), 2016, Volume 34, Issue 2, Article No. 7. [PDF] [Data&Code]
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GuoLong,Jie Tang and Juanzi Li. Semantic Mining of Social Networks. Morgan & Claypool Publishers, 2015. [DRAFT]
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GuoLong,Lei Shi, Hanghang Tong, Jie Tang, and Chuang Lin. VEGAS: Visual influEnce GrAph Summarization on Citation Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2015, Volume 27, Issue 12, Pages 3417-3431. [PDF] [Video Demo]
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GuoLong,Triadic Closure Pattern Analysis and Prediction in Social Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2015, Volume 27, Issue 12, Pages 3374-3389. [PDF]
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GuoLong,Jing Zhang, Zhanpeng Fang, Wei Chen, and Jie Tang. Diffusion of "Following" Links in Microblogging Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2015, Volume 27, Issue 8, Pages 2093-2106. [PDF]
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GuoLong,Jing Zhang, Jie Tang, Juanzi Li, Yang Liu, and Chunxiao Xing. Who Influenced You? Predicting Retweet via Social Influence Locality. ACM Transactions on Knowledge Discovery from Data (TKDD), 2015, Volume 9, Issue 3, Article No. 25. [PDF] [Code&Data]
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GuoLong,Jing Zhang, Jie Tang, Cong Ma, Hanghang Tong, Yu Jing, and Juanzi Li. Panther: Fast Top-k Similarity Search on Large Networks. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 1445-1454. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
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GuoLong,Yutao Zhang, Jie Tang, Zhilin Yang, Jian Pei, and Philip Yu. COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 1485-1494. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
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GuoLong,Yu Han and Jie Tang. Probabilistic Community and Role Model for Social Networks. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 407-416. [PDF] [Slides_PPT] [Slides_PDF] [Poster]
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Yuxiao Dong, Jing Zhang, Jie Tang, Nitesh V. Chawla, and Bai Wang. CoupledLP: Link Prediction in Coupled Networks. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 199-208. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
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GuoLong,Yang Yang, Yizhou Sun, Jie Tang, Bo Ma, and Juanzi Li. Entity Matching across Heterogeneous Sources. In Proceedings of the Twenty-First ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'15), pages 1395-1404. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Code&Data]
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GuoLong,Zhanpeng Fang and Jie Tang. Uncovering the Formation of Triadic Closure in Social Networks. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI'15), pages 2062-2068. [PDF] [Slides_PPT] [Slides_PDF] [Poster]
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GuoLong,Jie Tang, Zhanpeng Fang, and Jimeng Sun. Incorporating Social Context and Domain Knowledge for Entity Recognition. In Proceedings of the Twenty-Fourth World Wide Web Conference (WWW'15), pages 517-526. [PDF] [Slides_PPT] [Slides_PDF] [Code&Data]
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GuoLong,Jie Tang, Chenhui Zhang, Keke Cai, Li Zhang, and Zhong Su. Sampling Representative Users from Large Social Networks. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), pages 304-310. [PDF] [Slides_PPT] [Slides_PDF] [Data&Code]
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GuoLong,Yang Yang, Jie Tang, Cane Wing-Ki Leung, Yizhou Sun, Qicong Chen, Juanzi Li, and Qiang Yang. RAIN: Social Role-Aware Information Diffusion. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), pages 367-373. [PDF] [Slides_PPT] [Slides_PDF] [Data&Code]
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Yuxiao Dong, Yang Yang, Jie Tang, Yang Yang, and Nitesh V. Chawla. Inferring User Demographics and Social Strategies in Mobile Social Networks. In Proceedings of the Twentyth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'14), pages 15-24. [PDF] [Madness] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code] [Code Download] (Report by United Nations)
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Guo Long ,Mi Zhang, Jie Tang, Xuchen Zhang, Xiangyang Xue. Addressing Cold Start in Recommender Systems: A Semi-supervised Co-training Algorithm. In Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'14), pages 73-82. [PDF]
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Guo Long ,Jing Zhang, Jie Tang, Honglei Zhuang, Cane Wing-Ki Leung, and Juanzi Li. Role-aware Conformity Influence Modeling and Analysis in Social Networks. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 958-965. [PDF] [Poster] [Data&Code]
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Guo Long ,Yang Yang, Jia Jia, Shumei Zhang, Boya Wu, Qicong Chen, Juanzi Li, Chunxiao Xing, and Jie Tang. How Do Your Friends on Social Media Disclose Your Emotions? In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 306-312. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code]
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Guo Long ,Yang Yang, Walter Luyten, Lu Liu, Marie-Francine Moens, Jie Tang, and Juanzi Li. Forecasting Potential Diabetes Complications. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 313-319. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code]
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Zhigang Wang, Juanzi Li, Shuangjie Li, Mingyang Li, Jie Tang, Kuo Zhang, and Kun Zhang. Cross-lingual Knowledge Validation Based Taxonomy Derivation from Heterogeneous Online Wikis. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), pages 180-186. [PDF] [Poster] [Data]
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Guo Long ,Zhixin Li, Siqiang Wen, Juanzi Li, Peng Zhang, and Jie Tang. On Modelling Non-linear Topical Dependencies. In Proceedings of the 31st International Conference on Machine Learning (ICML'14), pages 458-466. [PDF]
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Guo Long ,Hong Huang, Jie Tang, Sen Wu, Lu Liu, and Xiaoming Fu. Mining Triadic Closure Patterns in Social Networks. In Proceedings of the Twenty-Third World Wide Web Conference (WWW'14), pages 499-504. [PDF] [Slides_PPT] [Slides_PDF]
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Guo Long ,Jie Tang, Sen Wu, and Jimeng Sun. Confluence: Conformity Influence in Large Social Networks. In Proceedings of the Ninteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'13), pages 347-355. [PDF] [Slides_PPT] [Slides_PDF] [Poster] [Data&Code] (Oral Presentation)
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Guo Long ,Yizhou Sun, Jie Tang, Jiawei Han, Cheng Chen, and Manish Gupta. Co-Evolution of Multi-Typed Objects in Dynamic Star Networks. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2014, Volume 26, Issue 12, Pages 2942-2955. [PDF]
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Guo Long ,Yi Cai, Ho-fung Leung, Qing Li, Hao Han, Jie Tang, Juanzi Li. Typicality-based Collaborative Filtering Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2014, Volume 26, Issue 3, Pages 766-779. [PDF]
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Guo Long ,Jing Zhang, Biao Liu, Jie Tang, Ting Chen, and Juanzi Li. Social Influence Locality for Modeling Retweeting Behaviors. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13), pages 2761-2767. [PDF] [Data&Code] [Poster]
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Guo Long ,Lei Hou, Juanzi Li, Xiaoli Li, Jiangfeng Qu, Xiaofei Guo, Ou Hui, and Jie Tang. What Users Care about: a Framework for Social Content Alignment. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13), pages 1401-1407. [PDF] [Data & Readme] [Slides_PDF] [Poster]
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Guo Long ,Tiancheng Lou and Jie Tang. Mining Structural Hole Spanners Through Information Diffusion in Social Networks. In Proceedings of the Twenty-Second World Wide Web Conference (WWW'13), pages 837-848. [PDF] [Slides_PPT] [Slides_PDF] [Data&Code]
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Guo Long ,Tiancheng Lou, Jie Tang, John Hopcroft, Zhanpeng Fang, Xiaowen Ding. Learning to Predict Reciprocity and Triadic Closure in Social Networks. ACM Transactions on Knowledge Discovery from Data (TKDD), 2013, Volume 7, Issue 2, Article No. 5. [PDF] [Code&Data] [System]
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Guo Long ,Jie Tang, Sen Wu, Jimeng Sun, and Hang Su. Cross-domain Collaboration Recommendation. In Proceedings of the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'12), pages 1285-1293. [PDF] [Slides_PDF Slides_PPT ] [Poster] [Data&Code] [System] [Video] (Full Presentation & Best Poster Award)
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Guo Long ,Jie Tang, Bo Wang, Yang Yang, Po Hu, Yanting Zhao, Xinyu Yan, Bo Gao, Minlie Huang, Peng Xu, Weichang Li, and Adam K. Usadi. PatentMiner: Topic-driven Patent Analysis and Mining. In Proceedings of the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'12), pages 1366-1374. [PDF] [Slides] [Poster] [System] [Video]
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Guo Long ,Rui Yan, Congrui Huang, Jie Tang, Yan Zhang, and Xiaoming Li. To Better Stand on the Shoulder of Giants. In Proceedings of the 2012 ACM/IEEE Joint Conference on Digital Libraries (JCDL'12), pages 51-60. [PDF] (Nominated as Best Student Paper)
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Guo Long ,Jie Tang, Tiancheng Lou, and Jon Kleinberg. Inferring Social Ties across Heterogeneous Networks. In Proceedings of the Fifth ACM International Conference on Web Search and Data Mining (WSDM'12), pages 743-752. (Plenary presentation) [PDF] [Slides] [Poster] [Data&Code]
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Guo Long ,Jie Tang, Yuan Zhang, Jimeng Sun, Jinghai Rao, Wenjing Yu, Yiran Chen, and ACM Fong. Quantitative Study of Individual Emotional States in Social Networks. IEEE Transactions on Affective Computing (TAC), 2012, Volume 3, Issue 2, Pages 132-144. [PDF] (Selected as the Spotlight Paper. Available here)
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Guo Long ,Jie Tang, A.C.M. Fong, Bo Wang, and Jing Zhang. A Unified Probabilistic Framework for Name Disambiguation in Digital Library. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2012, Volume 24, Issue 6, Pages 975-987. [PDF] [Data]
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Guo Long ,Bing He, Jie Tang, Ying Ding, Huijun Wang, Yuyin Sun, Jae Hong Shin, Bin Chen, Ganesh Moorthy, Judy Qiu, Pankaj Desai, David J. Wild. Mining relational paths in integrated biomedical data. PLOS ONE, 2011, 6(12). [PDF]
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Guo Long ,Jie Tang, Jing Zhang, Ruoming Jin, Zi Yang, Keke Cai, Li Zhang, and Zhong Su. Topic Level Expertise Search over Heterogeneous Networks. Machine Learning Journal, 2011, Volume 82, Issue 2, Pages 211-237. [PDF] [URL]
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Guo Long ,Jie Tang, Limin Yao, Duo Zhang, and Jing Zhang. A Combination Approach to Web User Profiling. ACM Transactions on Knowledge Discovery from Data (TKDD), 2010, Volume 5, Issue 1, Article 2. [PDF]
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Guo Long ,Wenbin Tang, Honglei Zhuang, and Jie Tang. Learning to Infer Social Ties in Large Networks. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD'11), pages381-397. [PDF] [Slides] [Data&Code] (Best Student Paper Runner-up)
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Guo Long ,Zi Yang, Keke Cai, Jie Tang, Li Zhang, Zhong Su, and Juanzi Li. Social Context Summarization. In Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'11), pages 255-264. [PDF]
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Guo Long ,Chenhao Tan, Lillian Lee, Jie Tang, Long Jiang, Ming Zhou, and Ping Li. User-level sentiment analysis incorporating social networks. In Proceedings of the Seventeenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'11), pages 1397-1405. [PDF] [Poster] (Top 4 cited papers among all KDD 2011's papers, More...)
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Guo Long ,Chenhao Tan, Jie Tang, Jimeng Sun, Quan Lin, and Fengjiao Wang. Social Action Tracking via Noise Tolerant Time-varying Factor Graphs. In Proceedings of the Sixteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'10), pages 1049-1058. [PDF] [Slides] [Data&Code]
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Guo Long ,Chi Wang, Jiawei Han, Yuntao Jia, Jie Tang, Duo Zhang, Yintao Yu, and Jingyi Guo. Mining Advisor-Advisee Relationships from Research Publication Networks. In Proceedings of the Sixteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'10), pages 203-212. [PDF] [Slides] [System] [Data&Code]
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Guo Long ,Jie Tang, Jimeng Sun, Chi Wang, and Zi Yang. Social Influence Analysis in Large-scale Networks. In Proceedings of the Fifteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'09), pages 807-816. [PDF] [Slides] [Data] [Code] (Top 4 cited papers among all papers published at KDD 2009-2013's, More...)
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Guo Long ,Jie Tang, Jing Zhang, Limin Yao, Juanzi Li, Li Zhang, and Zhong Su. ArnetMiner: Extraction and Mining of Academic Social Networks. In Proceedings of the Fourteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'08), pages990-998. [PDF] [Slides] [System] [API] [Citation Data] [DBLP Citation Data] [Author-Conference-Topic (ACT) Model (source code)] [More Data] (SIGKDD Test-of-Time Award, the 2nd most-cited paper among all KDD 2008's papers, More...)
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Guo Long ,Jie Tang, Hang Li, Yunbo Cao, and Zhaohui Tang. Email Data Cleaning. In Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'05), pages 489-499. [PDF] [Slides]
Knowledge Graph
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Guo Long ,Zhichun Wang, Juanzi Li, and Jie Tang. Boosting Cross-lingual Knowledge Linking via Concept Annotation. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13), pages 2733-2739. [PDF] [Poster]
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Guo Long ,Zhigang Wang, Zhixing Li, Juanzi Li, Jie Tang, and Jeff Z. Pan. Transfer Learning Based Cross-lingual Knowledge Extraction for Wikipedia. In Proceedings of the 51th Annual Meeting of the Association of Computational Linguistics (ACL'13), pages 641-650. [PDF] [Data & Readme]
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Guo Long ,Zhichun Wang, Juanzi Li, Zhigang Wang, and Jie Tang. Cross-lingual Knowledge Linking Across Wiki Knowledge Bases. In Proceedings of the Twenty-First World Wide Web Conference (WWW'12), pages 459-468. [PDF]
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Guo Long ,Juanzi Li, Jie Tang, Yi Li, and Qiong Luo. RiMOM: A Dynamic Multi-Strategy Ontology Alignment Framework. IEEE Transaction on Knowledge and Data Engineering (TKDE), 2009, Volume 21, Issue 8, Pages 1218-1232. (if =2.236) [PDF] [URL] (The 2nd most-cited paper among TKDE 2009-13's 500+ papers, More...)
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Guo Long ,Jie Tang, Ho-fung Leung, Qiong Luo, Dewei Chen, and Jibing Gong. Towards Ontology Learning from Folksonomies. In Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI'09), pages 2089-2095. [PDF] [Slides]
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Guo Long ,Qian Zhong, Hanyu Li, Juanzi Li, Guotong Xie, Jie Tang, and Lizhu Zhou. A Gauss Function based Approach for Unbalanced Ontology Matching. In Proceedings of the 2009 ACM SIGMOD international conference on Management of data (SIGMOD'09), pages 669-680. [PDF] [Slides]
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Guo Long ,Feng Shi, Juanzi Li, and Jie Tang. Actively Learning Ontology Matching via User Interaction. In Proceedings of the 8th International Conference of Semantic Web (ISWC'09), pages 585-600. [PDF] [Slides]
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Guo Long ,Jie Tang, Mingcai Hong, Juanzi Li, and Bangyong Liang. Tree-Structured Conditional Random Fields for Semantic Annotation. In Proceedings of the 5th International Conference of Semantic Web (ISWC'06), pages 640-653 [PPT] [PDF]
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Guo Long ,Jie Tang, Juanzi Li, Bangyong Liang, Xiaotong Huang, Yi Li, and Kehong Wang. Using Bayesian Decision for Ontology Mapping. Journal of Web Semantics, 2006, Volume 4, Issue 4, Pages 243-262. (if =3.41) [URL] [PDF] (Top 8 cited papers in JWS's history, More...)
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SERVICES Go Top
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Editor-in-Chief (EiC) of IEEE Transactions on Big Data (IEEE TBD)
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Editor-in-Chief (EiC) of ai open---a new AI journal for open and sharing
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Associate Editor:
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Past Associate Editor:
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Conference/Workshop Organization:
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General Co-Chair of The Web Conference 2023 (WWW'23)
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Program Co-Chair of The Web Conference 2021 (WWW'21)
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General Co-Chair of the 24th Conference on Innovation in Clouds, Internet and Networks (ICIN'21)
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Tutorial Co-Chair of The Web Conference 2020 (WWW'20)
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KDDCUP Co-Chair of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'20)
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Sponsor Co-Chair of The Web Conference 2019 (WWW'19)
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Program Co-Chair of The 8th CCF International Conference on Natural Language Processing and Chinese Computing (NLPCC'19)
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Associate General Chair of the 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'18)
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"Sister Conference Best Paper Track" Chair of the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI'18)
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AI Web Track (Intelligent and Autonomous systems on the Web) Chair of the 27th International Conference on World Wide Web (WWW'18)
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Video and Streaming Co-Chair of the 23th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'17)
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Research Track Program Co-Chair of the 25th ACM International Conference on Information and Knowledge Management (CIKM'16)
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Video and Streaming Co-Chair of the 22th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'16)
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Program Co-Chair of the 8th ACM International Conference on Web Search and Data Mining (WSDM'15)
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Program Co-Chair of The 2015 International Conference on Social Network Analysis and Mining (ASONAM'15)
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KDD CUP Co-Chair of the 21th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'15)
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Poster Co-Chair of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'14)
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Data Co-Chair of the 8th International AAAI Conference on Weblogs and Social Media (ICWSM'14)
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Tutorial Co-Chair of the 7th ACM International Conference on Web Search and Data Mining (WSDM'14)
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Workshop Co-Chair of The 2014 International Conference on Social Network Analysis and Mining (ASONAM'14)
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Vice Program Co-Chair of the 12th IEEE International Conference on Data Mining (ICDM'13)
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Tutorial and workshop organization chair of the 23th International Joint Conference on Artificial Intelligence (IJCAI'13)
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Workshop Co-Chair of the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'13)
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Poster Co-Chair of the 12th IEEE International Conference on Data Mining (ICDM'13)
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Workshop Co-Chair of the 7th ACM Conference on Recommender Systems (RecSys'13)
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Tutorial Co-Chair of The 2013 International Conference on Social Network Analysis and Mining (ASONAM'13)
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Local Chair of the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'12)
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Program Co-Chair of The 2012 International Conference on Social Informatics (SocInfo'12)
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Tutorial Co-Chair of The 2012 International Conference on Social Network Analysis and Mining (ASONAM'12)
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Publications Co-Chairs of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'11)
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Program Chair of the 7th International Conference on Advanced Data Mining and Applications (ADMA'11)
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Publicity Co-Chair of the 11th IEEE International Conference on Data Mining (ICDM'11)
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Poster Chair of the 4th ACM International Conference on Web Search and Data Mining (WSDM'11)
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Area Chair of the 2011 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD'11)
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Panel Chair of the 4th edition of the successful IEEE International Conferences on Cyber, Physical and Social Computing (CPSCom'11)
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Publicity Co-Chair of the Third International Conference on Social Informatics (SocInfo'11)
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Vice Program Chair of the 2011 IEEE/WIC/ACM International Conference on Web Intelligence (WI'11)
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Vice Program Chair of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence (WI'10)
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Registration Chair of ASWC'06
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Co-Chair of Workshop SWSM'11 on SIGIR'11, MDS'11 on SIGKDD'11, LDMTA'11 on SIGKDD'11, LDMTA'10 on SIGKDD'10, LDMTA'09 on ICDM'09, SWSM'09 on CIKM'09, Financial Data Mining (FDM'09), SWSM'08 on WWW2008.
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(S)PC Member:
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2022: WSDM'22 (SPC)
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2021: SIGKDD'21 (SPC), ICML'21 (Area Chair), NeurIPS'21 (Area Chair), IJCAI'21 (Area Chair), CIKM'21 (SPC), SDM'21 (SPC), ECML/PKDD'20 (SPC)
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2020: SIGKDD'20 (SPC), SDM'20, ICML'21, ECML/PKDD'20 (SPC), WWW'20 (SPC), ASONAM'20
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2019: SIGKDD'19 (SPC), NIPS'19, ICML'19, IJCAI'19 (SPC), WWW'19, WSDM'19 (SPC), ASONAM'19
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2018: WSDM'18 (SPC), IJCAI'18, SIGIR'18,
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2017: SIGKDD'17 (SPC), AAAI'17 (SPC), ICWSM'17 (SPC), WSDM'17 (SPC), WWW'17, IJCAI'17, SIGIR'17
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2016: SIGKDD'16 (SPC), WSDM'16, ICWSM'16 (SPC), ASONAM'16
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2015: SIGKDD'15 (SPC), IJCAI'15 (SPC), ICWSM'15 (SPC), ICDM'15 (Area Chair), SDM'15, ICDE'15
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2014: SIGKDD'14 (SPC), ICDM'14 (Area Chair), WSDM'14, SDM'14, ICWSM'14, ASONAM'14 (SPC)
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2013: SIGKDD'13 (SPC), IJCAI'13 (SPC), WWW'13 (Social Networks, Content Analysis, Bridging structured and unstructured data), SIGIR'13, WSDM'13, SDM'13, ICWSM'13 (SPC), CIKM'13, SAC'13 (SPC), DASFAA'13.
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2012: SIGKDD'12, WWW'12 (Tutorial, Web Mining, Social Networks, Demo), AAAI'12, SIGIR'12, ICDM'12, ICWSM'12 (SPC), ISWC'12 (SPC).
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2011: SIGKDD'11, WWW'11, AAAI'11, WSDM'11, ICDM'11, ISWC'11 (SPC), ICMLA'11 (SPC), EMNLP'11, DASFAA'11, ASONAM'11, WAIM'11, DEXA'11.
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2010: SIGKDD'10, SIGIR'10, WWW'10 (DM&ML track), ACL'10, COLING'10, ICDM'10, WSDM'10, ISWC'10, EMNLP'10, DASFAA'10, WI'10, DEXA'10, ISDPE'10, ASONAM'10, CloudCom'10, INCoS'10.
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2009: SIGIR'09, SDM'09, DEXA'09, WISE'09, WI'09, IUI'09, ASONAM'09, ICCCI'09, NLPIR4DL'09, MCPC'09, CISIS'09, CASoN'09, APWeb-WAIM'09, KDIR'09, CloudCom'09, AIRS'09, ACM RecSys'09, SAW'09, ICIS'09, CSWS'09, WSM'09, WISM'09-AICI'09, ASWC'09, OEDM'09.
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2008: IJCNLP'08, SAW'08, WWW'08 Poster Session, NIMC'08, SOCASE'08, PGSC'08, SNA-KDD'08, ASWC'08, WI'08, IWCSN'08, OAEI'08(SPC).
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AWARDS AND HORNORS Go Top
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2020 ACM SIGKDD Test-of-Time Award
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2020 WangXuan Distinguished Young Scholar
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2018 ACM SIGKDD Service Award
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2018 NSFC Distinguished Young Scholar
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2017 First Prize of Beijing Science and Technology
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2016 Microsoft Research Asia Collaborative Research Award
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2015 Newton Advanced Fellowship Award
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2013 First Prize of Chinese Association of AI (CAAI)
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2012 NSFC Excellent Young Scholar
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2011 Beijing Science and Technology Star
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2011 SCOPUS National Youth Science Star
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2010 Tsinghua Academic New Star Award
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2012 JCDL Best Student Paper Nomination
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2011 PKDD Best Student Paper Runnerup
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2016 Best employee of DCST, Tsinghua University
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2012 Best employee of DCST, Tsinghua University
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2011 Best employee of Tsinghua University
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2011 Best employee of DCST, Tsinghua University
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2007 Best employee of DCST, Tsinghua University
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The 2006 Excellent PhD Thesis of Tsinghua University
TALKS Go Top
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Keynote about Representation Learning on Networks to be given at ASONAM'19
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Keynote about AI driven MOOCs given at EDM'17
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Invited talk about academic knowledge graph given at WSDM'16
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Keynote about social network mining given at SocInfo'15


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SERVICES Go Top
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Editor-in-Chief (EiC) of IEEE Transactions on Big Data (IEEE TBD)
-
Editor-in-Chief (EiC) of ai open---a new AI journal for open and sharing
-
Associate Editor:
-
Past Associate Editor:
-
Conference/Workshop Organization:
-
General Co-Chair of The Web Conference 2023 (WWW'23)
-
Program Co-Chair of The Web Conference 2021 (WWW'21)
-
General Co-Chair of the 24th Conference on Innovation in Clouds, Internet and Networks (ICIN'21)
-
Tutorial Co-Chair of The Web Conference 2020 (WWW'20)
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KDDCUP Co-Chair of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'20)
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Sponsor Co-Chair of The Web Conference 2019 (WWW'19)
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Program Co-Chair of The 8th CCF International Conference on Natural Language Processing and Chinese Computing (NLPCC'19)
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Associate General Chair of the 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'18)
-
"Sister Conference Best Paper Track" Chair of the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI'18)
-
AI Web Track (Intelligent and Autonomous systems on the Web) Chair of the 27th International Conference on World Wide Web (WWW'18)
-
Video and Streaming Co-Chair of the 23th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'17)
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Research Track Program Co-Chair of the 25th ACM International Conference on Information and Knowledge Management (CIKM'16)
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Video and Streaming Co-Chair of the 22th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'16)
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Program Co-Chair of the 8th ACM International Conference on Web Search and Data Mining (WSDM'15)
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Program Co-Chair of The 2015 International Conference on Social Network Analysis and Mining (ASONAM'15)
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KDD CUP Co-Chair of the 21th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'15)
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Poster Co-Chair of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'14)
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Data Co-Chair of the 8th International AAAI Conference on Weblogs and Social Media (ICWSM'14)
-
Tutorial Co-Chair of the 7th ACM International Conference on Web Search and Data Mining (WSDM'14)
-
Workshop Co-Chair of The 2014 International Conference on Social Network Analysis and Mining (ASONAM'14)
-
Vice Program Co-Chair of the 12th IEEE International Conference on Data Mining (ICDM'13)
-
Tutorial and workshop organization chair of the 23th International Joint Conference on Artificial Intelligence (IJCAI'13)
-
Workshop Co-Chair of the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'13)
-
Poster Co-Chair of the 12th IEEE International Conference on Data Mining (ICDM'13)
-
Workshop Co-Chair of the 7th ACM Conference on Recommender Systems (RecSys'13)
-
Tutorial Co-Chair of The 2013 International Conference on Social Network Analysis and Mining (ASONAM'13)
-
Local Chair of the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'12)
-
Program Co-Chair of The 2012 International Conference on Social Informatics (SocInfo'12)
-
Tutorial Co-Chair of The 2012 International Conference on Social Network Analysis and Mining (ASONAM'12)
-
Publications Co-Chairs of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'11)
-
Program Chair of the 7th International Conference on Advanced Data Mining and Applications (ADMA'11)
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Publicity Co-Chair of the 11th IEEE International Conference on Data Mining (ICDM'11)
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Poster Chair of the 4th ACM International Conference on Web Search and Data Mining (WSDM'11)
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Area Chair of the 2011 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD'11)
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Panel Chair of the 4th edition of the successful IEEE International Conferences on Cyber, Physical and Social Computing (CPSCom'11)
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Publicity Co-Chair of the Third International Conference on Social Informatics (SocInfo'11)
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Vice Program Chair of the 2011 IEEE/WIC/ACM International Conference on Web Intelligence (WI'11)
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Vice Program Chair of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence (WI'10)
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Registration Chair of ASWC'06
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Co-Chair of Workshop SWSM'11 on SIGIR'11, MDS'11 on SIGKDD'11, LDMTA'11 on SIGKDD'11, LDMTA'10 on SIGKDD'10, LDMTA'09 on ICDM'09, SWSM'09 on CIKM'09, Financial Data Mining (FDM'09), SWSM'08 on WWW2008.
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(S)PC Member:
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2022: WSDM'22 (SPC)
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2021: SIGKDD'21 (SPC), ICML'21 (Area Chair), NeurIPS'21 (Area Chair), IJCAI'21 (Area Chair), CIKM'21 (SPC), SDM'21 (SPC), ECML/PKDD'20 (SPC)
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2020: SIGKDD'20 (SPC), SDM'20, ICML'21, ECML/PKDD'20 (SPC), WWW'20 (SPC), ASONAM'20
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2019: SIGKDD'19 (SPC), NIPS'19, ICML'19, IJCAI'19 (SPC), WWW'19, WSDM'19 (SPC), ASONAM'19
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2018: WSDM'18 (SPC), IJCAI'18, SIGIR'18,
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2017: SIGKDD'17 (SPC), AAAI'17 (SPC), ICWSM'17 (SPC), WSDM'17 (SPC), WWW'17, IJCAI'17, SIGIR'17
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2016: SIGKDD'16 (SPC), WSDM'16, ICWSM'16 (SPC), ASONAM'16
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2015: SIGKDD'15 (SPC), IJCAI'15 (SPC), ICWSM'15 (SPC), ICDM'15 (Area Chair), SDM'15, ICDE'15
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2014: SIGKDD'14 (SPC), ICDM'14 (Area Chair), WSDM'14, SDM'14, ICWSM'14, ASONAM'14 (SPC)
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2013: SIGKDD'13 (SPC), IJCAI'13 (SPC), WWW'13 (Social Networks, Content Analysis, Bridging structured and unstructured data), SIGIR'13, WSDM'13, SDM'13, ICWSM'13 (SPC), CIKM'13, SAC'13 (SPC), DASFAA'13.
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2012: SIGKDD'12, WWW'12 (Tutorial, Web Mining, Social Networks, Demo), AAAI'12, SIGIR'12, ICDM'12, ICWSM'12 (SPC), ISWC'12 (SPC).
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2011: SIGKDD'11, WWW'11, AAAI'11, WSDM'11, ICDM'11, ISWC'11 (SPC), ICMLA'11 (SPC), EMNLP'11, DASFAA'11, ASONAM'11, WAIM'11, DEXA'11.
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2010: SIGKDD'10, SIGIR'10, WWW'10 (DM&ML track), ACL'10, COLING'10, ICDM'10, WSDM'10, ISWC'10, EMNLP'10, DASFAA'10, WI'10, DEXA'10, ISDPE'10, ASONAM'10, CloudCom'10, INCoS'10.
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2009: SIGIR'09, SDM'09, DEXA'09, WISE'09, WI'09, IUI'09, ASONAM'09, ICCCI'09, NLPIR4DL'09, MCPC'09, CISIS'09, CASoN'09, APWeb-WAIM'09, KDIR'09, CloudCom'09, AIRS'09, ACM RecSys'09, SAW'09, ICIS'09, CSWS'09, WSM'09, WISM'09-AICI'09, ASWC'09, OEDM'09.
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2008: IJCNLP'08, SAW'08, WWW'08 Poster Session, NIMC'08, SOCASE'08, PGSC'08, SNA-KDD'08, ASWC'08, WI'08, IWCSN'08, OAEI'08(SPC).
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AWARDS AND HORNORS Go Top
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2020 ACM SIGKDD Test-of-Time Award
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2020 WangXuan Distinguished Young Scholar
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2018 ACM SIGKDD Service Award
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2018 NSFC Distinguished Young Scholar
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2017 First Prize of Beijing Science and Technology
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2016 Microsoft Research Asia Collaborative Research Award
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2015 Newton Advanced Fellowship Award
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2013 First Prize of Chinese Association of AI (CAAI)
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2012 NSFC Excellent Young Scholar
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2011 Beijing Science and Technology Star
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2011 SCOPUS National Youth Science Star
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2010 Tsinghua Academic New Star Award
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2012 JCDL Best Student Paper Nomination
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2011 PKDD Best Student Paper Runnerup
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2016 Best employee of DCST, Tsinghua University
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2012 Best employee of DCST, Tsinghua University
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2011 Best employee of Tsinghua University
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2011 Best employee of DCST, Tsinghua University
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2007 Best employee of DCST, Tsinghua University
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The 2006 Excellent PhD Thesis of Tsinghua University
TALKS Go Top
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Keynote about Representation Learning on Networks to be given at ASONAM'19
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Keynote about AI driven MOOCs given at EDM'17
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Invited talk about academic knowledge graph given at WSDM'16
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Keynote about social network mining given at SocInfo'15
R&D team led by Professor Guolong

A real-time classification method of health and disease biosignals based on biocompatible AI chips. They use a polymer-based fiber network whose structure is similar to the human brain and implement the neuromorphic artificial intelligence principle of energy storage calculations. The random arrangement of polymer fibers forms a so-called "recursive network" that enables it to process data, similar to the human brain. The non-linearity of these networks allows it to amplify even the smallest signal changes that are often difficult for doctors to assess—in the heartbeat, for example. However, using the non-linear transformation of the polymer network makes it possible without any problems.
However, so far, success has been limited to simple electronic components such as a single synapse or sensor. So far, it has been impossible to solve complex tasks. In our research, we have now taken a crucial step towards realizing this vision. By using the power of neuromorphic computing, we have not only successfully solved complex classification tasks in real time, but we will also be able to do it in the human body. This method will make it possible for us to develop further intelligent systems in the future to help save human lives.
Japan Offices
ABOUT US
We are alums of Intel and Silicon Graphics; techies from MIT; entrepreneurs from Silicon Valley;
big believers in technology’s potential; bigger believers in human potential.
Above all, we are people who have been in your shoes.
Advanced science and technologyDNA





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We work on some of the most complex and interesting challenges in AI.
Our world-class research has resulted in hundreds of peer-reviewed papers, including in Nature and Science.
EXPLORE OUR RESEARCH ACROSS:
Advanced science and technologyDNA
Technical field
Agri-Bio
Drug discovery
Medical / welfare
environment
energy
Manufacturing technology
material
Device / device
machine
Civil construction
Electronic
communication
information
measurement
analysis
others
Business domain *
Agriculture
Fishing
material
energy
environment
construction
real estate
Housing
logistics
Mobility
device
robot
universe
Finance
retail
Travel / Sightseeing
IT / advanced technology
communication
application
media
Advertising / marketing
content
medical care
health care
Childcare
education
nursing
business
Human resources
Administration
law
Hood
Sports
Entertainment
Fashion / beauty
Health is a global, award-winning provider of health information technology, advancing population health and precision medicine solutions for the delivery of care across the entire health ecosystem. Founded in 1993, Health’s focus for 27 years has been on delivering software, services and support for healthcare organisations that empower clinicians and caregivers with the right information to deliver the best possible care.
We specialise in open technology systems that seamlessly integrate all forms of health and personal data across the entire health community and present that data back to users in real time to provide optimum patient care. We believe that software needs to do more than serve up data; it needs to provide insights in real time to the people who need it, when they need it. We provide a smart suite of solutions that enable clinicians to extract meaningful insights and make more accurate decisions about patient care. Delivering patient-centred healthcare and quality health outcomes that help patients live a healthier life.
Health employs 500+ people in 20 offices across 13 countries. Our technology is used by hundreds of thousands of clinicians across the globe to manage the health care of more than 100 million patients. With the most widely deployed population health management platform globally; more than 55 large-scale (regional and country-wide) solutions successfully deployed in over 15 countries, we provide the world’s number one health information platform.
To revolutionise global healthcare so every individual receives the perfect care for them.
What does our future vision of healthcare look like? Imagine a world where patients receive the perfect care for them. Where they are at the centre of their own healthcare, making key care decisions themselves, supported by research, education and the guidance of their trusted circle of care including family and physicians.
This is a world where information is easily shared between caregivers and clinicians, to ensure that patients receive the best healthcare possible. Individuals will have the tools to keep themselves well and monitor their progress, sharing any sign of deterioration or concern with their circle of care to ensure immediate preventative action.
With advances in genomics and DNA sequencing, the potential to practice preventative medicine based on predictive modelling is enormous. Precision Medicine starts now. Information gleaned about an individual's health from their DNA and other factors such as their environment, family history and social situation are immensely powerful to determine the best treatments they should receive throughout their lifetime to maximise their chances of staying well and preventing serious illness from developing.
Health's solutions capture the vast amounts of health data available and provide the tools to support healthcare professionals and health insurers who manage their members' wellness programmes to make more effective decisions - through applying analytics and employing care management and patient engagement.
At Health, we are excited to revolutionise healthcare, delivering modern technology to ensure that every individual receives the perfect care for them.
If we could make sense of health data for an entire population, patterns could be identified and evidence about the most successful medicines or treatments could be used to create an optimised care plan for an individual. There would be rapid, scalable, precise and accurate diagnostics as well as the understanding of each individuals biology and genetic make-up to apply the most effective course of action. Keeping people healthy would in turn help reduce the need for expensive interventions such as emergency department visits, hospitalisations, imaging testing and procedures, reducing costs to the healthcare system.
Precision Medicine is the platform for Population Health Management and Precision Medicine that provides healthcare professionals with the real-time cognitive support they need to make the best possible decisions at the point of care.
The open platform scales to accommodate the vast amount of data generated by new models of care, to support the journey from population health management to precision medicine. Precision Medicine's API management layer allows third party developers to build new capabilities on the platform, creating an innovative healthcare ecosystem.
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Robust privacy capability
An advanced, granular privacy capability provides controlled access to patient information based on user roles and the sensitivity of patient data.
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combines Orion Health’s extensive data integration and HIE experience with modern technology and a distributed architecture to handle massive volumes of high-velocity data.
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Foundation platform for population health and precision medicine
Through seamless integration with our care management and patient engagement applications, Amadeus allows you to proactively identify, manage, and transition at-risk patients in real time.
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Intelligent modelling
enables predictive modeling that identifies and stratifies the at-risk patients in a population and provides the data to drive rapid decision-making.
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Adapts to new models of care
Drawing patient-centric data to Amadeus enables healthcare organisations to make informed decisions regarding the move from traditional payment to alternative payment models. Payers, ACOs, and other organisations involved in value-based models can support their participating providers with value- added services.
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Supports innovation with APIs and BI interfaces
provides secure access to all its data via APIs and ANSI SQL interfaces to Orion Health, as well as third-party, applications.
Key Features
Access all types of patient data in one place
Data domains aggregate clinical, claims, consumer, and other healthcare data types (such as social determinants, family history, device and omics data) into well-defined data models that expand the longitudinal health record.
Capture and store massive volumes of data
Built using the latest storage technologies and a distributed processing architecture, Amadeus is unparalleled in its ability to extract maximum value from today’s data and prepare organisations for exponential data growth.
Extract future value from data collected today
The Data Lake is an annotated archive, retaining all source data in its original form. Organisations can focus on their immediate needs, safe in the knowledge that all data is being retained for future analysis and enhanced modelling.
Configure a data domain specifically for your business
Custom data domains enable bespoke data models to be designed by subject-matter experts and deployed through simple user interface.
Machine learning integrated to workflow
provides a central platform to host validated machine learning models. It supplies one place to manage the lifecycle of algorithms and models and ensure their long-term applicability, accuracy and performance with its robustgovernance and monitoring tools and practices.
Interoperability with the HL7® FHIR® standard APIs
supports FHIR (Fast Healthcare Interoperability Resources) APIs, innovative HL7 REST services for accessing discrete information. The platformallows third-party developers to access the rich data and services in real time through its API management layer and open, REST-based APIs.
Knowledge Hub
Precision medicine is an emerging model of healthcare that combines all information unique to an individual, and identifies prevention and treatment strategies that will be effective for them based on genetic, environmental and lifestyle factors.
At Health, we’re on a mission to make precision medicine a reality worldwide. The quantity of data coming from even a limited number of sources cannot be managed through traditional technologies and will require highly scalable and flexible data spaces to connect, analyse and manage them. We have launched Amadeus, a precision medicine platform built on modern, open technology that will provide clinicians with the cognitive support they need to make the best decisions possible. We enable the delivery of precision medicine by aggregating, storing, and making sense of all forms of data, so that we can transform healthcare from being about many, to focusing on one.
Precision medicine Amadeus is uniquely designed to future proof you for evolving models of healthcare, from population health management to precision medicine. It combines Health's extensive data integration experience and a distributed architecture to handle massive volumes of high velocity data, combining a comprehensive range of data models including clinical, claims, consumer, and genomic, with powerful custom data modelling capability.
Once all the relevant data is combined, the next step is to analyse that data to gain valuable insights that are then actioned through workflow tools to deliver personalised care plans and patient engagement strategies for every individual.
In the evolving healthcare economy, new specialised applications and devices are emerging every day to support better health outcomes. That’s why at Orion Health we provide streaming access to all our data in Amadeus via APIs. Third parties can innovate and develop applications on our platform to tailor care for individuals, and truly realise precision medicine.
AWS is Health’s cloud-based platform of choice
Due to its scalable and resilient infrastructure, AWS is Orion Health’s cloud-based platform of choice. Health on AWS provides our clients with secure access to a private cloud healthcare solution stack delivered as a SaaS Model. Powered securely from a remote cloud infrastructure, this model removes the operational burden and costs associated with a data centre. Benefits include accelerated time to market, improved monitoring capabilities and utilisation of the strictest security protocols, all whilst reducing the risk of human error and lowering costs. The flexible and scalable solution can be tailored to an organisation's needs and integrated into existing support structures.





Issue a carbon reduction bill achieve carbon neutrality with a technical route
Climate change is already one of the most severe challenges facing global development. The group recently released the carbon reduction bill "Towards a Zero-Carbon Era". In the context of China’s efforts to achieve a peak in carbon emissions in 2030 and achieve carbon neutrality by 2060, Alibaba Group will comprehensively accelerate research on low-carbon cutting-edge technologies. Promote a green and low-carbon lifestyle in an all-round way, and protect the natural and ecological environment like protecting the eyes.
Cheng Li, chief technology officer of Alibaba Group, said that the orderly advancement of carbon peaks and carbon neutral goals will bring about technological system changes and is likely to give birth to new technological innovations and cooperation. At present, from the perspective of technological innovation, we can see at least three levels of carbon reduction, which are to achieve emission reduction in the development of enterprises; to help platform enterprises and industries to decarbonize; and to promote low-carbon consumption and environmental protection with a larger radiation range.
"Introduce a carbon neutral technology development roadmap as soon as possible. To achieve carbon neutrality, we must take a technical route. This is not a single level of struggle, it requires the joint efforts of the whole society."
Technology to achieve carbon neutrality
The carbon reduction bill proposes a low-carbon model, that is, if all servers in China adopt liquid cooling technology, the electricity saved in one year is close to the total annual power generation of the Three Gorges Dam; if the express delivery smart packing algorithm is popularized Most of China’s 50 billion parcels can lose weight; if the idle items in the home can be fully circulated, a mobile recycling factory will reduce the carbon footprint of users.
When the world's first computer ENIAC was born, someone predicted that the potential high cost would make the global demand for computers no more than five. But now, when large-scale data centers become general computing power bases, how to decarbonize computing technology and use technology to solve the problems caused by technological development has become the global focus.
The Internet economy should become a low-carbon economy. In the past few years, Cloud has been committed to building the infrastructure of the digital economy era and continuously striding forward to low-carbon production. In 2020, Yun's self-built super data center will trade 410 million kilowatt-hours of clean energy, a year-on-year increase of 266%, and reduce carbon dioxide emissions by 300,000 tons, a year-on-year increase of 127%.
The data center is the world's largest submerged liquid-cooled server cluster. Its servers are immersed in a special coolant. The power usage effectiveness (PUE) is close to the theoretical limit of 1.0. It can save 70 million kilowatt-hours of electricity each year. All street lights around the West Lake will be continuously lit for 8 years; while the Guangdong Heyuan Data Center, which uses deep lake water cooling, will achieve 100% use of green and clean energy in 2022, becoming the group's first super data center to achieve carbon neutrality.
In 2020, Yun's self-built super data center will trade 410 million kilowatt-hours of clean energy, a year-on-year increase of 266%, and reduce carbon dioxide emissions by 300,000 tons, a year-on-year increase of 127%.
Together with customers to achieve carbon neutrality
After the outbreak of the new crown epidemic, the Group has made efforts to build digital infrastructure to help small and medium-sized enterprises reduce costs and improve efficiency, while also working with enterprises to move towards green and environmental protection. The steel industry solution developed by Cloud assisted Pangang Group currently saves 1.28 kg of iron per ton of steel produced, and is expected to save 17 million yuan in steelmaking costs each year; Alibaba Cloud has assisted the waste incineration power generation company Hanlan to improve the environment 23% combustion stability; as of the end of 2020, Dingding paperless office has reduced carbon emissions by 11 million tons, which is equivalent to planting about 6 million trees and solidifying 6,300 square kilometers of desert.
Ele.me has sent a total of about 400 million orders without tableware, reducing carbon emissions by 6,400 tons.
Promote green and low-carbon consumption
The group has been committed to promoting green and low-carbon consumption for many years. Since 2014, Cainiao has used more than 100 billion parcels with electronic face sheets, saving about 400 billion pieces of paper and saving about 20 billion yuan in cost. Green recycling bins have covered 315 cities in 31 provinces, autonomous regions, and municipalities in China, more than 100 million cartons are recycled. Ele.me has sent a total of about 400 million orders without tableware, reducing carbon emissions by 6,400 tons.
In 2020, users will put about 1 billion idle items on shelves, and idle circulation will turn more waste into consumption. Since 2017, idle fish has recycled more than 50,000 tons of used clothes, about 23.7 million old books, 3.66 million mobile phones, and 145 large household appliances. Ten thousand units; Yintai Miaojie saved about 1,600 tons of paper through paperless cash register and electronic invoice and receipt. A green consumption of the whole life cycle from consumption to logistics to idle transactions is taking shape.
Footprints keep abreast of the latest development trends of the Group, and learn about new trends in emerging topics such as innovative technology, e-commerce and smart logistics through news stories and feature articles.

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• The HOCIT Group has contributed to the realization of a sustainable society by solving social issues through products and services that utilize ICT. However, in recent years, global social issues have become more serious, and group-wide efforts to resolve them have become increasingly important.
• Therefore, in September 2016, the HOCIT Group expressed its support for the United Nations Sustainable Development Goals (SDGs). At the same time, each group company is working to achieve the goals by associating the 17 goals of the SDGs with their own businesses.
• For example, at the “HOCIT Group CSR Conference,” which is held every year to raise awareness of CSR among employees, examples of group companies solving social issues through their business activities are shown in relation to the 17 goals of SDGs. By sharing it as an "excellent CSR measure," we are instilling in our employees the awareness that "daily business activities and CSR are one."
• In addition, the content of employee training related to CSR has been reviewed based on the SDGs, and e-learning is used to educate employees within the group.
• Going forward, he will continue to boost the momentum for achieving his SDGs through various initiatives, not only utilizing his own products and services, but also through the realization of Smart World and Society 5.0 through collaboration of technology and knowledge with partners, the SDGs Contribute to achievement.

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Partner
Our partner Technische Universität Dresden; TUD

scientists develop implantable AI platform for real-time biosignal classification
Artificial intelligence (AI) will fundamentally change medicine and healthcare: Diagnostic patient data, e.g. from ECG, EEG or X-ray images, can be analyzed with the help of machine learning, so that diseases can be detected at a very early stage based on subtle changes. However, implanting AI within the human body is still a major technical challenge. TU Dresden scientists at the Chair of Optoelectronics have now succeeded for the first time in developing a bio-compatible implantable AI platform that classifies in real time healthy and pathological patterns in biological signals such as heartbeats. It detects pathological changes even without medical supervision. The research results have now been published in the journal 'Science Advances'.
Research and development of a system for high-speed cell analysis and separation in real time using innovative AI in the field of regeneration and cell medicine
By irradiating cells with special structured lighting, structural information converted to one dimension is acquired in a short time, and cells identified in real time are identified by a machine learning (AI) model created from the acquired data. Separation in a microfluidic device with reduced cell damage.
Since this data analysis approach eliminates the need to reconstruct the image for human recognition, it is possible to separate cells while performing structural analysis at high speed, and it has not been easy for the human eye to distinguish them. It will also be possible to identify the cells. Therefore, it is possible to separate cells that had to be stained with an antibody or the like for selection marks by the conventional method without staining. In addition to the fields of regenerative medicine and cell medicine, it is expected to be used to bring about innovation in the fields of drug discovery and in vitro diagnosis.
Started joint development of cell analysis / separation system for practical use of cell analysis / separation technology utilizing AI. By combining the technology of ThinkCyte to separate cells at high speed and with high accuracy without staining, the know-how to operate Hitachi's equipment stably, and mass production technology, it is possible to achieve unstaining, which was difficult with existing cell separation technology. We aim to realize high-speed, high-precision cell separation with a device that operates stably with good reproducibility, and aim for stable and low-cost mass supply of cells, which is an issue in the field of regeneration and cell medicine. This makes it possible for pharmaceutical companies to stably produce large quantities of regenerative and cell-based drugs, which contributes to the reduction of manufacturing costs.
• Developed a high-precision automatic analysis system for blood cell morphology using AI deep learning technology
• Successful differential diagnosis of blood diseases by AI automatic analysis system
• Aiming for automation of blood morphology test and practical application of AI screening diagnostic support
We have developed AI blood cell morphology automatic analysis technology that realizes automation of morphological examination, which has been a long-standing issue in the field of examination, and highly accurate discrimination technology for specific diseases. We have developed an AI analysis system that enables highly accurate automatic identification of blood cells by analyzing blood cell images of various diseases using artificial intelligence (AI) deep learning technology (* 1). Furthermore, this AI analysis system uses myelodysplastic syndrome (MDS) (* 2), which is a neoplastic blood disease, and aplastic anemia, which is a non-neoplastic blood disease, based on the morphological information of blood cells that appear in a specific disease. We have demonstrated that differential diagnosis of sexual anemia (AA) (* 3) is possible. This result has shown the way to the automation of blood morphology test and the practical application of screening diagnosis support by AI automatic analysis technology.
We showed the distribution of 17 types of blood cells captured by the AI blood cell automatic analysis system using t-SNE (t-distributed stochastic neighborhood embedding), which is a machine learning algorithm that visualizes high-dimensional data. The blood cell clusters identified by AI are color-coded. From this distribution map, cells for each origin of blood cells such as granulocytic cells (lobed nucleus neutrophils, SNE to promyelinocytes, PMY) and lymphocytes (lymphocytes, LY and reactive lymphocytes, VLY) The clusters are formed, and it can be seen that AI accurately captures the characteristics of cell morphology. By using this analysis system, it has become possible to distinguish between blood cell morphological abnormalities in MDS cases and AA cases.
Furthermore, using this AI automatic analysis system, blood cell images of MDS cases and AA cases were comprehensively analyzed, and features such as the frequency of occurrence of morphological abnormalities were extracted. Next, using the extracted features, we performed an analysis by the gradient boosting method (* 4), which is one of the AI technologies. Finally, as a result of verifying the differential diagnosis ability of MDS and AA by the AI blood cell automatic analysis system, it became clear that it has extremely high-precision diagnostic ability (sensitivity 96.2%, specificity 100.0%).
As described above, we were able to show the possibility of automating blood morphology test by AI automatic analysis system and practical application of AI screening diagnosis support.
* 1 Deep learning technology: Artificial intelligence technology consisting of neural networks with many deep layers. Deep Convolutional Neural Networks (Deep CNNs) and others have been devised based on human vision and are demonstrating excellent performance in the field of image recognition.
* 2 Myelodysplastic syndrome (MDS): A disease in which normal blood cells cannot be produced due to abnormalities in hematopoietic stem cells in the bone marrow. Blood cell depletion and morphological abnormalities occur. It is a neoplastic disease and may develop into leukemia.
* 3 Aplastic anemia (AA): A non-neoplastic disease in which hematopoietic stem cells in the bone marrow are damaged and blood cells decrease.
* 4 Gradient boosting method: A machine learning algorithm that realizes highly accurate prediction and discrimination.
We have constructed an analysis technology that allows AI to read more than 2,000 images of white blood cells as learning images and classify them into 5 to 6 types such as lymphocytes and eosinophils based on the cell shape. When the classification results were verified with white blood cells for 72 healthy people, it was possible to analyze with high accuracy with a correct answer rate of 99 to 85% depending on the classification method.
In order to use this technology as the basic technology for regenerative medicine and cell medicine manufacturing, we will promote cooperation with pharmaceutical companies and research institutes that develop and manufacture regenerative medicine products in Japan and overseas, including North America, where great demand is expected. We also aim to contribute to the development of the regenerative medicine market by incorporating safe and highly reliable equipment into the value chain of regenerative medicine by utilizing the high-speed digital processing technology cultivated through the development of information and communication technology of the Group. ..
We have been researching and developing a technology that analyzes each cell in detail and at high speed without staining, and separates only the target cells with high accuracy. Although such cell measurement / analysis technology is an important technology that is the basis of life science research and medical treatment such as disease diagnosis, it is difficult to achieve both the amount of information acquired from a single cell and the separation rate. There, this compatibility is realized
Our partner
· Science, Technology and Innovation (STI) for implementing the SDGs
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· In September, 2015, the United Nations General Assembly unanimously adopted the 2030 Agenda for Sustainable Development that comprise of 17 Sustainable Development Goals (SDGs) and 169 targets. The SDGs provide the universal goals to the issues the world including Japan and the humanity faces. The goals and targets of the SDGs are relevant to the implementation of Super Smart Society, "Society 5.0" (Forth Industrial Revolution), set by the 5th Science and Technology Basic Plan as a major pillar of the Japan's Plan for Dynamic Engagement of All Citizens for the strategic growth as well as to the basic principle of our international cooperation.
· The First annual Multistakeholder Forum on Science, Technology and Innovation for the SDG (STI Forum) was held on 6-7 June 2016, at the UN Headquarters in New York, aiming to address how the Science, Technology and Innovation (STI) could contribute to the implementation of the SDGs ("STI for SDGs"). It is highly expected that, to achieve the SDGs, the STI play an indispensable role by resolving various emerging issues we face and by providing scientific data and analysis for better political decision.
· It is indeed crucial that all stakeholders from government, universities, research agencies and institutes, NGOs and private sectors, etc. take transformative steps in a holistic manner toward STI for SDGs. As Japan Science and Technology Agency promotes not only the research and development (R&D) but also plans R&D strategies as well as enhance science communication, science education and open data, we are taking inclusive initiatives nationally and internationally for achieving the SDGs.
· Basic Policies on the Contribution of Science, Technology and Innovation for the Achievement of the Sustainable Development Goals (STI for SDGs) at Japan Science and Technology Agency (Edited Version)
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World-class data service provider for AI learning.
Based on data resources, technical capabilities and abundant data processing experience, we have provided high-quality data services to more than 1,000 artificial intelligence companies and research institutes worldwide since our establishment.
In the development of ICT technology and its applications, materials, hardware, and so on.
R & D of software, in this field, IoT / M2M / sensor / high-speed communication / big data / AI / deep learning / self
Dynamic operation / robot / xR / security / quantum computer, etc.
In this field, the material itself has peculiarity or superiority and is expected to innovate industry and society.
What is done, new materials that promote the utilization of new energy resources, protect the environment or
Emphasis is placed on materials that contribute to the reduction of carbon dioxide. Also, the raw materials related to them
Technology that leads to energy saving and low environmental load in industrial processes
The agri-bio industry is an industry that has the potential to expand into a wide range of fields, not just food and food.
Research and development related to increasing production and securing stability of biomass resources, which is a common issue, is also an important issue.
think. Economic efficiency, consideration for the environment, response to ethical, legal and social issues, integrated technology with IoT and AI
In other words, the mechanism and method for the future, which is not directly related to the product, has been dramatically improved.
It is also an important point of view to let them do it. In recent years, "genome editing technology" has appeared, and it is a frequent and accurate remains.
As a method that enables gene recombination, it has opened up great potential for animal and plant breeding.
We believe that this will bring about new developments in the production of substances by living organisms.
Furthermore, climate warming countermeasures are an urgent issue on a global scale, such as chemical products and bio-raw materials for fuels.
Biotechnology is once again in the limelight as a manufacturing technology. That scientific rationale
In the concept of Life Cycle Assessment (LCA) as an evaluation method, 2050 carbon neutral
From the perspective, new concepts are required.
In this field, plant factories / biopesticides / functional feeds / high-yielding varieties / disease-resistant varieties, functional foods / food safety
All / safety / quality control / guarantee, functional materials / high-performance biomolecules / utilization of biological functions / biomimetics
/ Biodegradability, photosynthesis, health, environment, biological database, cell analysis, growth measurement, biomanufacturing process
(Scale up, downsizing) will be the foundation of the agri-bio industry with keywords such as
It covers a wide range of themes related to technology.
· Partner
· KIOXIA, PwC Japan, Samsung Electronics
· Ajinomoto Group ’
· Advantest, AIOCORE, DIC Corp., Hitachi, Honda Tsushin Kogyo, IBIDEN, I-PEX, MIRISE, OKI Electronics, Peers, Sumitomo Corp. Kyushu, Toyo Inc SC, UNIADEX
· Tohoku University, AIST, NIED, PETRA, PIDA
· , Fujitsu NVIDIA Dell (DELL) Shionogi Pharmaceutical
· AMD
· [Osaka University x Komatsu Ltd.
· [Ibaraki University x Fuji Oil Group Headquarters Co., Ltd.
· [Nagoya University x Tier IV, Inc.]
· The University of Tokyo x SoftBank Corp.
· Kyoto University Original Co., Ltd.
· Shinshu University]
· Yamagata University]
· Kobelco Construction Machinery Co., Ltd.
· [Shionogi Pharmaceutical Co., Ltd.]
· [AGC Inc.
· [Daikin Industries, Ltd.
· JX Nippon Mining & Metals Co., Ltd.
· [Hitachi, Ltd.]
· [NEC Corporation]
· 【Panasonic Corporation】
· [Nitto Denko Corporation]
· [Nippon Telegraph and Telephone Corporation (NTT)]
· [Ube Industries, Ltd.]
· [Chugai Pharmaceutical Co., Ltd.]
· Tateisi Science and Technology Foundation (OMRON Corporation)]
· Murata Science Foundation (Murata Manufacturing Co., Ltd.)]
· Professor Emeritus, Hokkaido University
· National Science Foundation (NSF)
· University of Notre Dame
· Kyoto University
· University of California, Berkeley
· Baylor University
· Tokyo Institute of Technology
· Portland State University
· Collaboration with UK Research and Innovation (UKRI)
· University of Leeds Transportation
· University of Glasgow
· Oxford University
· National Center for Child Health and Development
· French National Research Organization (ANR)
· National Center for Scientific Research (CNRS) Research
· University of Paris (Descartes) School of Medicine
· Sophia University
· National Institute of Information and Communications Technology Auditor
· Sonire Therapeutics Co., Ltd.
· DeNA Co., Ltd.
· Nippon Telegraph and Telephone Corporation
· Bandai Namco Online Co., Ltd.
· NTT DoCoMo, Inc.
· NTT Communications Corporation
· Kose
· Casio
· daiwahouse
· Chiba University Hospital
· East Japan Railway Company SmartNews Co., Ltd.
· Otsuka Shokai
· Hewlett-Packard Japan Co., Ltd.
· Yonyou (UFIDA)
· Kingsoft Co., Ltd.
· Shenzhen Kingdee
· Sunyard (Sunyard, Nobumasa)
· China Soft International
· Beijing Chuka Red Flag Software Technology Co., Ltd. (Red Flag Linux)
· Neusoft Group
· Hisoft Technology (International) Group Company (Hisoft)
· Dalian Hi-Think Computer (DHC)
· Hirohiko Science and Technology (Beyondsoft)
· Soft Stone
· Adobe Systems
· Google (Android)
· Dassault Systèmes (Catia)
· HP
· IBM
· Microsoft
· Oracle
· SAP AG
· Sybase
· NEC
· Fujitsu
· Hitachi
· NTT DATA
· NSD Co., Ltd.
Fujitsu Group
Hitachi Group
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Finance
• Bank
• Trust
• stock
• credit card
• Life insurance
• Non-life insurance
service
• Press
• Information service
Manufacturing
• car
• Electronics
• Pharmaceuticals
• Machine
• Food
• Chemistry
Commercial
• Trading company
• Retail
construction
• Construction
• real estate
• Housing
• Building management
transportation
• Railroad
• Aviation
• Land transportation
communication
• communication
• mobile
public
• Government agency
• Municipal
• public facility
• Electricity and gas
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Research and Development
Regenerative medicine using cell sheet technology and creation of cultured meat
Sound insulation earmuffs using measurement technology with MEMS differential pressure sensor & acoustic metamaterial
Sentience modeling based on information theory
Keio Medtech Design-Learning from COVID-19 emergency response through manufacturing-
Possibility of environmental transfer technology "MONIQUA" -Construction of artificial coral reef ecosystem
Hack cells with mechanical stimulation! ?? ~ Mechanical stimulation, prescription ~
Cell culture, tactile rendering, soft robotics-The future pioneered by actuator technology-
Soft Animaloid White Christmas Edition
Science of "light energy" pioneered by edge laser spectroscopy
Brain science of language: Approaching the mystery of language with linguistics x brain science
Affect mechanism that opens up from neuroscience
Manipulate freely to make, carry, and break-Gel as an artificial biomaterial
The world's fastest plastic optical fiber forefront
Stealth type electronic artificial skin
Digitization and inheritance of professional technology and automation of manufacturing sites
Global environment-first manufacturing
Fusion of smart real stores and EC
Shopping experience that suits individual lifestyles and behaviors
Shift from treatment to preventive care
More personalized healthcare services
Realization of smart city
Online administrative services
Data-driven management-Transformation of corporate activities using data
Improving productivity and engagement through work style reforms
Providing value by integrating global standard services (SAP, Salesforce, etc.) with your own industry knowledge
Cloud integration-total support service from planning to operation of the optimal cloud environment
Integrated collaboration platform that connects both real and digital
Technical field
Agri-Bio
Drug discovery
Medical / welfare
environment
energy
Manufacturing technology
material
Device / device
machine
Civil construction
Electronic
communication
information
measurement
analysis
others
Smart city
Regional revitalization
Circular economy
D & I (Diversity & Inclusion)
MaaS
Agriculture
Renewable energy
Battery industry
Experts who can hear in the next-generation energy / carbon neutral area
Business domain *
Agriculture
Fishing
material
energy
environment
construction
real estate
Housing
logistics
Mobility
device
robot
universe
Finance
retail
Travel / Sightseeing
IT / advanced technology
communication
application
media
Advertising / marketing
content
medical care
health care
Childcare
education
nursing
business
Human resources
Administration
law
Hood
Sports
Entertainment
Fashion / beauty
Affiliated academic society
ACM
IEEE
AAAI
ASA
ISCA
APA
Japanese Society for Artificial Intelligence
Information Processing Society of Japan
Institute of Electronics, Information and Communication Engineers
Acoustical Society of Japan
Japanese Society of Speech Society
Linguistic Society of Japan
Association for Natural Language Processing
Japan Children's Society
Japan Baby Society
Early childhood education
Learning system
Developmental disability
welfare
Support for persons with disabilities
Developmental psychology
Cognitive science
Cognitive model
Behavioral science
Knowledge representation
study
Common sense reasoning model Intention Situation understanding Emotion
Phonetics
Linguistics
Speech language processing
Dialogue model
Multimodal computer vision communication
Brain science
Neurophysiology
Exercise science



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Supports 4 types of SDGs such as SDGs, environmental problems, and measures against plastic removal [Biodegradation / Wooden / BIO / Recycling] Food loss reduction Alternative food Environmental services Eco products / materials
Renewable energy consultants in the field of renewable energy such as solar cells, batteries, and hydrogen production
Under the corporate philosophy of "accelerating the social implementation of technology," we will contribute to the business improvement and business growth of our customers through co-creative DX consulting. It is a service that acquires and accumulates external data that has not been fully utilized, such as SNS, events, and weather data, in real time, adds original analysis processing by AI, and provides it with API. Correspondence such as weather forecast / warning, power generation forecast / demand forecast / surplus forecast, electricity rate plan linkage, JEPX price linkage, etc. A service that scientifically and accurately predicts new corona infection from satellite image analysis.
Providing upcycling of local resources and CO2 reduction by walking DX. Unique 3D map engine for picking up trash from Matinaka and the coast. .. The data provided can be used for various initiatives such as inventory reduction and automation. From the field of business practice to demand forecasting by cutting-edge AI, please use the data you do not have yet as your weapon. Utilizing water power generation technology, we are engaged in product development, sales, OEM, etc. We have registered more than 20 patents (including international patents). Currently, it is being promoted as a response to blackouts including local governments and hospitals. We are developing the sustainable D2C brand "Cannature" for small lot processed foods that we co-create and develop with small-scale producers, restaurants, and processed food manufacturers. It contributes to the reduction of food loss by using scraps and non-standard products that are produced in the manufacturing process. , A platform for solving the big social problem of "food loss". We deliver up to 97% off products from sponsor manufacturers with a high awareness of social contribution to our members, and donate part of our sales to social contribution organizations such as environmental protection, animal protection, and food banks. For SDGs and sustainability. Meals, also known as compatible plant-based foods, have a low environmental impact as well as human health, so their recognition / needs are increasing worldwide. "SOL Pareto Service" that separates oils and fats from factory wastewater and uses fuel so that such plant-based foods can be eaten simply by chilling them in a range. "High-pressure vacuum dehydrator" ★ [Drainage GX] solves the problem of wastewater and sludge treatment We will contribute to SDG and ESG efforts with a low-cost and eco-friendly two-fluid nozzle and mist generator. [Countermeasures against heat of workers and liftmen at manufacturing sites and distribution sites] [Countermeasures against infectious diseases] [Countermeasures against static electricity / drying] Products using [eco-friendly and low-cost mist] that helps to realize a safe and secure working environment I would like to introduce you.
[Heat / heat stroke countermeasure products]
・ Mist cooler for forklift operators. Cool the liftman with an environmentally friendly mist. It is a mist cooler that allows you to work comfortably while feeling the cool breeze with a fine mist. It is a little wet outdoors and dry mist indoors to improve the environment of the site where it is difficult due to the intense heat.
Introducing the latest technology, a gas detection camera that can be installed in a drone to "visualize" gas leaks from the sky. It is possible to efficiently, quickly and safely detect leaks of dangerous flammable gas from the sky through equipment inspections of plants and factories, emergency investigations in the event of a disaster, etc. It can contribute to the digitization of crisis management and the promotion of DX, and is expected to greatly contribute to disaster prevention and mitigation.
In addition, because it visualizes greenhouse gases such as methane, it is also very effective for carbon neutrality, which is an initiative for SDGs.
[Detectable gas]
Acetic acid, ammonia, benzene, butadiene, butane, ethane, ethylbenzene,
Ethylene, heptane, hexane, isoprene, methylethylketone, methane,
Methanol, MIBK, octane, pentane, propane, propylene, sulfur dioxide,
Toluene, vinyl chloride, xylene
[Corresponding drone]
Matrice 200 V2 / Matrice 210 V2 / Matrice 210 RTK V2 / Matrice 300 RTK
We provide an IoT data dashboard service that can centrally manage various sensor information. By centrally managing on-site data such as data acquired from sensors, work status, and photographs taken in the cloud, we have reduced the work that people had to face and check, and realized the efficiency of on-site work. increase.
[Recommended sensor device]
■ Low power consumption IoT camera
It is an LTE-equipped camera device that operates continuously for about 3 years without the need for a power supply. No power supply or network work is required, it can be used simply by installing it at the inspection site, and history monitoring using photographs can be realized reasonably. It has been introduced at various sites such as remote monitoring of construction sites and remote monitoring of bird and beast traps.
■ Composite weather sensor
A network-compatible meteorological observation system that emphasizes environmental resistance, accuracy, and reliability based on a low power consumption data logger (recorder). It is possible to measure by combining 8 elements of weather (temperature, humidity, wind direction, wind speed, solar radiation, rainfall, atmospheric pressure, snow cover) according to the measurement purpose and conditions.
Create a sustainable future! We will introduce services that are close to DX in various fields by using IT technology, using new ways of enjoying food, goods, energy and services using AR / VR. I want to create a new service that suits your new lifestyle! I want to make existing services online and virtual! It is a service that fulfills such wishes. Bring two-way communication online. The operation design is friendly to both the management side and the visitor side. It is widely used for in-house events, exhibitions, to B / to C, and so on. PPA service development one step ahead of the introduction of renewable energy
■ More than 3800 achievements such as RE100 ■ CDP certified provider ■ Re-energy ratio industry top class [About SDGs projects starting from stations]
In the "SDGs project starting from the station", we set goals to support from the 17 goals of SDGs on a monthly basis, introduce the supporting companies that are working on SDGs activities with digital signage, and donate to station users. We are looking for. Donations can be made from the terminal installed next to the digital signage for 100 yen at a time, and in conjunction with the donation, an animation will be played on the digital signage according to the goals of the SDGs, and the collected donations will be sent to the activity groups related to the SDGs as a credit fee. All donations will be made except for. This is the first time in Japan that a fund-raising digital signage has been introduced. [About the Kansai / Food SDGs Project]
The "Kansai / Food SDGs Project" is based on Kansai and is registered in the co-creation challenge of the "TEAM EXPO 2025" program at the Osaka / Kansai Expo by the West Japan Cooking School Association and Ad Kintetsu Co., Ltd. It will be the first co-sponsored project
In this project, the "wasteful spirit" that has been in the food culture of Japanese food and Kansai since ancient times and the cooking technology that uses all the ingredients are reconsidered as "food SDGs", and "food SDGs" through the most familiar home cooking. Aim to learn. Create an opportunity for all people who cook to re-recognize the "SDGs spirit of food" that resides in Kansai's food culture, disseminate Kansai's food culture from Kansai to the world, and further develop Japanese food culture. I will connect.
There are two major project initiatives. The first is an initiative to disseminate information on Kansai's food culture and food SDGs centered on the project website, and the second is a new qualification system to learn food SDGs based on Kansai's food culture. It is the founding of "Sustainable Cooking Test". This project is an initiative to enliven the 2025 Osaka / Kansai Expo from the local area / Kansai, and will disseminate "Kansai's food culture" and "food SDGs" through "co-creation" with partners who agree with the purpose of recruiting in the future. We aim to create new initiatives. We provide "decarbonized solutions" to meet various needs, from power generation business to electricity storage / supply and demand management and green power supply. Utilizing technologies such as AI technology to solve green power issues
Currently, we are looking for supporting companies who can support this project. For supporting companies, we will post the company name and logo on the housing panel, introduce the efforts of SDGs on the special HP, broadcast the video about SDGs of the supporting companies in the signage, etc. I will do it.
Next-generation human resources development type SDGs consulting to become a company of choice from the future ◆
The SDGs are vague and it is difficult to get an image of the connection with management and business. I don't know what to start with. I think there are many companies that have such problems.
Because we have many years of experience in supporting education through industry-academia-government collaboration, we provide careful and easy-to-understand consulting on SDGs that are difficult to understand. It is necessary for each employee to change their behavior in order to effectively promote the SDGs, rather than formalizing them only by the management and promotion departments.
We plan a human resources development program tailored to your company's issues and support the introduction of SDGs that encourage employee behavior change. Introducing next-generation human resources development-type SDGs so that all employees can participate while having fun and become a company of choice from the future
(1) For companies: Planning and development of new employee training and young / mid-career employee training for software development companies, engineer training consulting
(2) For educational institutions: Science and technology / engineering / information education materials, curriculum, teacher guidance
③ For cram schools and after-schools: classroom opening, curriculum development consulting
④ For home study: Robot programming teaching material development
⑤ Event: Planning and management of regional, national and global robot contests
⑥ Next-generation human resources development: SDGs consulting, D & I training, DX innovation human resources development project planning and management.











We are a climate tech company aiming to realize a decarbonized society through innovation utilizing digital technology.
We will form a professional group of digital technology, data science, and energy, and become a "carbon-neutral digital partner" of society and companies aiming for decarbonization.
We are working on the following three main services to realize a "carbon-neutral" society.
(1) Construction of a mechanism to optimally use energy with digital technology
・ Energy optimization cloud service
Utilizing Big Data and AI, we will develop services that streamline electricity market price forecasting, energy use, distributed power source (storage battery, solar power, etc.) operation, and electric vehicle operation, and provide them as cloud services. ..
(2) Providing eco-friendly clean electricity with zero CO2 emissions and 100% renewable energy
Aiming to build a mechanism for effective use of clean energy and a mechanism to purchase clean energy at a low price, we offer a virtually zero emi menu with a non-fossil certificate at a low price (currently deployed in the Kyushu region).
(3) Digital: Supports everything from DX planning to system installation and operation. PoC implementation and DX consulting for new services
We mainly support digital transformation for energy companies. We provide total support from company-wide digitalization strategies to the establishment of new work styles such as digital design and development of operations, design thinking and agile development.
・ Solution introduction
We design and build systems such as salesforce installation (CRM construction) and cloud service (AWS) installation. We also carry out web construction and mobile development.
・ Innovation human resources development training
Digital, design thinking, logical thinking, etc.
Providing various trainings for developing human resources who can think and promote innovation, etc.
We are making efforts to produce and develop Japanese DX human resources.
It is a venture company that faces the solution of corporate issues and social issues by building both smart factories and smart energy. We are developing the following businesses with the desire to promote smart manufacturing by combining "latest products and services," "best technology," and "optimal methods," and to become the backbone that supports the Japanese economy.
① Comprehensive support business for realizing smart factories
--Smart factory construction production and consulting
--Planning and sales of smart factory packages such as robot systems for the manufacturing industry
--Equipment operation monitoring / failure prediction, production simulator, production simulator introduction and utilization service
Making full use of digital technology, we provide one-stop services from the conception to launch and operation of large-scale smart factory projects, such as the conversion of existing equipment to IoT, in collaboration with affiliated companies and manufacturers with which we have a collaborative relationship.
(2) Comprehensive support project for realizing smart energy
--Sales of renewable energy power generation element parts
--Renewable energy power plant property introduction, sales, media management
――Proposal and sales of solutions associated with it
In addition, we provide optimal solutions from the perspective of "energy" when making smart factories. Energy management utilizing "renewable energy" that realizes energy saving and energy creation leads to stable production.
[World-class technological capabilities]
Affiliated company wins 3rd place in the world at World Robot Summit 2018
[Building a smart factory in Shenyang, China]
A smart factory construction project with state-of-the-art processing and assembly equipment is underway. Not only an actual production factory, but also a base that leads future manufacturing such as research and development and education.
[Focusing on engineer education to support the growth of Southeast Asia]
We aim to develop businesses and connect with culture from a medium- to long-term perspective by facing contributions to society and improvement of social structure rather than immediate profits. As part of this, he is currently instructing a project to develop motivated human resources in China, Vietnam, and Myanmar into first-class engineers. By stimulating each other with Japanese engineers, we will create a chemical reaction for growth.
Currently, with the tailwind of decarbonization and digitization, "Forbes Japan January 2021 issue" Super Entreprenuers 200 (200 companies listed at once! Japanese startup encyclopedia) "selected" "Nikkei Trendy February issue" future market The types and scale of services are rapidly expanding, such as being selected as one of the 100 companies that make products.
Also, on November 10, 2021,
Started EV charge shift demonstration experiment utilizing V2H automatic control technology linked to market price. Pressed "Charge shift demonstration project of electric vehicle by dynamic pricing" by Ministry of Economy, Trade and Industry, Agency for Natural Resources and Energy. It is an indispensable service for future energy problems, optimizing EV charging based on four AI predictions and realizing automatic control of V2H devices using IoT technology.
Momentum for a sustainable society is increasing, as lifestyles and SDGs are attracting attention.
Since its founding, we have been developing businesses centered on reuse, but in addition to providing many options for consumers seeking smart consumption, we at Market Enterprise Group are sustainable through the construction of sound-cycle distribution. We continue to take on the challenge of building a society and growing into an indispensable corporate group for society that can solve many problems in Japan and overseas.
Currently, we will also establish an offshore development base in Vietnam to accelerate the introduction of IT.
The era of mass production and mass consumption has come to an end, and we seek wisdom in consumption.
A new community centered on agriculture and food
Increase the value of services to promote food loss reduction
A new community centered on agriculture and food
With the mission of "continuing to be a social good company" that solves social issues, we aim to be "the company that reduces food loss most in Japan."
Social contribution type We sell food products that are normally discarded before the expiration date and deliver them to our users. One of the characteristics of the business is that a part of the sales is donated to environmental protection groups and social welfare groups. The total amount of donations since the company was founded is about 65 million yen.
Through our food loss reduction business, we are building a system that contributes to solving a wide range of social issues.
About 6.43 million tons of food are thrown away
With the mission of continuing to be a social good company, we aim to be the company that reduces food loss the most in Japan.
Japan is one of the world's leading food loss nations.
Despite the low food self-sufficiency rate and relying on imports for about 60%, it is still edible due to strict distribution control based on "one-third rule" *, dirt on packages, scratches, and other business practices. A large amount of food is wasted.
The amount is about 6.43 million tons. It's the same calculation that all the people throw away a bowl of rice every day. Through a social contribution food sharing platform, we will reduce food loss in Japan by half.
* Rule to divide the period from the date of manufacture of food to the expiration date into three equal parts and set the delivery deadline and sales deadline.
SDGs adopted by the United Nations
From the beginning, we have placed "proactive social contribution" and "problem-solving ability to generate profits as a business" as important values. We believe that a sustainable system (business) is an essential solution to social issues. In order to realize this, we value "individuality" including working styles so that each member's "desire to help people" = "social engine" can be fully demonstrated. While understanding and supporting each other's feelings and situations, we will push forward at full speed in a fun and energetic manner. We would like to continue to be an organization where business people who want to provide value to society gather and work hard together.
It has been launched and is growing rapidly with the support of the times.
We would like to achieve discontinuous growth toward the solution of social issues and the further leap forward as a service.
To a product that is easier to use for the increasing number of users every day
And in order to evolve into a product that can quickly solve the problems of business partners
Dedicated responsibility to promote product development
"Inventory analysis cloud system to change the retail industry from scratch to solve the world's mass disposal problem
Creating a sustainable society with SDGs x DX
Achievements in commercializing "water pipe deterioration diagnosis AI"
Business development to scale SaaS products for the industrial waste industry
In order to "solve the world's mass disposal problem," we are developing and operating SaaS to solve inventory problems in the retail industry such as apparel with AI.
It is a system that allows apparel companies to increase sales and profits without mass production and without extra inventory.
Not only apparel companies but also retailers in other industries are introducing it.
Best technology x Best UX
In order to automate the extremely complicated vehicle dispatching work of the industrial waste industry and provide it to users who are unfamiliar with the use of IT services, we are developing services with a small number of elites with the goal of realizing "best technology x best UX". going. We place great importance on the production of high-quality products, and both the UX / UI designer and CEO and the optimization engineer and CTO are involved in product production.
◆ Creating an organization where engineers can play an active role
We have created an environment where engineers can work on development with high motivation.
And the field of solving inventory problems is not limited to retail. We are strengthening our business foundation to cover the supply chain from wholesalers to raw material manufacturers.
The inventory problem is the "lifeline of retail companies." It is said to be a problem directly related to management.
The representative Segawa once ran an e-commerce business for children's clothing, and was born from the actual experience of overcoming the three bankruptcy crises faced by inventory through data analysis.
Many retailers have huge unsold inventory in remote warehouses that employees don't usually see. Moreover, the tens of millions of inventory data are often aggregated in Excel, and the reality is that it takes a lot of effort and time to manage and analyze.
We provide that time and means to help solve essential inventory problems. for example
・ Daily visualization of inventory risks in remote warehouses
・ The demand forecast shows the number of products to be purchased.
・ Automation of selection of sale products, which used to take time manually
By using the time gained in this way for new sales strategies,
・ Customer unit price increased by 8%, inventory halved
・ Sales increased by 25%, deposit balance 2.1 times
A happy case has been reported.
◆ Introduction results
Three years after its release, it has been introduced mainly by enterprise companies.
Dome (UNDER ARMOUR), ASICS Japan, Onward Kashiyama
3coins PAL GROUP Holdings, haco!
Inquiries have increased 10 times and sales (ARR base) have increased 50 times in the last year even with Corona. Business content ■
・ SDGs consulting
Hearing about the current situation of customers and what they should be, we provide consulting for SDGs by backcasting. We provide one-stop support from promoting understanding of SDGs to setting goals, business integration, and subsequent follow-up.
・ New business consulting
Consistently back up new business creation with high uncertainties.
We will take a steady approach from all angles over a period of at least half a year.
・ Web production / application development
We propose design and development to achieve the purpose from the goal and budget that the customer aims at.
We provide a wide range of services related to system development from marketing measures, not just production.
■ Growth potential and future prospects ■
Achieved more than double the year-on-year growth and is steadily expanding. Recently, media exposure has increased, and we have received nearly 10 times as many inquiries as last year.
In the future, while aiming to be listed, we will scale up our business and organization, and at the same time, we will be a hub in the SDGs area.
We aim to be a key player in the industry that connects partners with each other so that we can be present.
Developed "LIMEX", a "new material from Japan that replaces plastic and paper" that uses limestone as the main raw material (patented in Japan and overseas). Raised more than 13 billion yen in total. One of the few Japanese unicorn companies (in 2019, Nihon Keizai Shimbun "NEXT Unicorn Survey", we became the sixth unicorn company in history in Japan, and in 2020, we are the third largest in Japan (estimated corporate value 123.3 billion). (Ranked in Yen)), we are growing at an accelerating pace with the aim of becoming the world's top player in the sustainability business area.
Now that the heat is rising for the sound material-cycle society, the shift to the circular economy, and resource and environmental problems.
In collaboration with Bioworks, a group company that develops plant-derived plastic materials, we decided to launch a new EC that handles products using environment-friendly materials. With D2C, we will create sustainable values directly for toC customers. Please participate in the launch of EC, which is a collection of domestic ethical products.
□ Business □ ■■
"Limestone", which is abundant in the world (100% self-sufficient in Japan), has a low risk of depletion compared to oil, water, forests, etc. used when manufacturing plastics and paper, and is useful from the viewpoint of resource consumption. Is the main ingredient of LIMEX. We are working on the development of materials that enable resource conservation and reduction of environmental impact such as CO2 throughout the life cycle of the product procurement, manufacturing, and processing processes. LIMEX products are mainly used in plastic substitute products such as LIMEX Bag, and are used by more than 5,200 companies such as major companies and government agencies. (Haneda Airport, Disney Store, Yoshinoya, etc.) In addition, in order to popularize recyclable LIMEX materials, we are promoting the creation of a recycling-oriented model by forming partnerships between local governments and companies.
In addition to the LIMEX business, we are developing "Circulex," a material containing 50% or more of recycled materials, in order to promote resource recycling as the recycled plastic market expands due to the waste plastic problem.
■■ □ Global expansion □ ■■ Received the Social Impact Award at Plug & Play, one of the three major accelerators in China and Silicon Valley. He has won the Japan-US Innovation Award at Stanford University and the "Grand Prize" in the Exceptional Growth category at EY Entrepreneur of the Year 2019 Japan. In addition, we have introduced 100% renewable energy power to our Shiraishi factory (production base), and now we are
Since it is possible to produce LIMEX and mold plastic substitute products fabless using existing equipment in Japan and overseas, we are also strengthening overseas production and are focusing on building a supply chain for local production for local consumption. The initiative was elected to the COP, an international conference on climate change, as a delegation of the Japanese government, and I had the opportunity to publicize the project at the G20 last year.
Proposal of SDGs project strategies for foreign-affiliated and listed companies
・ Planning and support for regional revitalization projects
・ Publishing support for vegan restaurants, product development planning
・ Development of sustainable disaster prevention goods with our own products
・ Support for campaign planning of global environmental conservation group projects
A consulting company that creates new businesses through the introduction and promotion of SDGs. Utilizing the projects and know-how that we have worked on so far, we aim to solve social and management issues while mixing digital, analog and data.
Through "work," we are creating social infrastructure for people with difficulty working to play an active role.
(1) BPO business specializing in persons with disabilities (2) EC / D2C specialization type and in-house customized logistics center (EC (3) Public-private partnership business are being developed.
Our company serves as a platform and connects workers with disabilities (working continuation support offices, etc.) with private companies and local governments that want to outsource work.
Currently, employment continuation support establishments and employment transition support establishments nationwide are operated with national financial resources, and people with difficulty working go to facilities to work, but they work at very low hourly wages. The current situation is that there is.
This is due to the inability of each facility to focus on marketing and sales to private companies to acquire jobs.
Therefore, in order to create a "distribution of work" with our company as a platform, we have partnered with business offices nationwide to create a database of what the people with difficulty in employment are good at and what they can do.
Based on that, we sell to private companies and subcontract the ordered work to a team of people with disabilities.
We have acquired many needs from private companies, such as data entry and correction of EC sites and mail-order shipping agency.
Workers with disabilities can work on their favorite jobs, and provide "work" that makes them feel rewarding and self-growth as well as working conditions.
[Details of business details]
① BPO business specializing in people with disabilities)
We have networked more than 15,000 workers with disabilities and more than 1,500 offices nationwide, matching a total of 500 types of jobs received from private companies and more than 1,300 jobs, and creating new "opportunities for active participation" for people with difficulty working. This model has been evaluated and expected by the domestic public sector, and was adopted by the JICA (Japan International Cooperation Agency) project in 2021.
(2) EC (EC / D2C specialized type, in-house customized logistic center)
As a micro-fulfillment model that is attracting particular attention from overseas startups, we provide a dedicated logistic center to D2C operators.
As the EC / D2C market continues to grow rapidly, there is an overwhelming shortage of logistic centers and human resources. We provide original logistic centers for D2C operators by utilizing our network of workers with disabilities working nationwide and more than 1,000 offices.
③ Public-private partnership business
Through cooperation agreements with local governments, we will develop our business in close contact with the local community.
Currently, we are collaborating with 5 local governments, and over the next 5 years, we will realize cooperation with all 47 prefectures.
■ Business content ■
・ SDGs consulting
Hearing about the current situation of customers and what they should be, we provide consulting for SDGs by backcasting. We provide one-stop support from promoting understanding of SDGs to setting goals, business integration, and subsequent follow-up.
・ New business consulting
Consistently back up new business creation with high uncertainties.
We will take a steady approach from all angles over a period of at least half a year.
・ Web production / application development
We propose design and development to achieve the purpose from the goal and budget that the customer aims at.
We provide a wide range of services related to system development from marketing measures, not just production.
■ Growth potential and future prospects ■
Achieved more than double the year-on-year growth and is steadily expanding. Recently, media exposure has increased, and we have received nearly 10 times as many inquiries as last year.
Going forward, we aim to be a key player in the industry that connects partners with each other so that we can become a hub in the SDGs domain while expanding our business and organization with the aim of listing.
■ Rescue people who are forced to drop out unwillingly by nature with the power of business ■ Members who have felt uncomfortable since childhood due to unreasonableness, discrimination, unfairness due to the environment, etc. in the world are gathering increase.
We are seriously thinking of aiming for a better society by facing the same direction as the SDGs set as the global goal.
The SDGs are also a promise to the Earth in 2030.
Our goal is to realize our promises to the future, pass on a sustainable society to the future, and ensure that "zero people are suffering from nothing wrong".
■ Strengths ■
Our strength is to provide strong technology consulting while controlling social issues, management issues, and educational issues.
Rather than presenting strategies and analyzes based solely on data and numerical values, the experience value of in-house projects and business creation supports the high quality of proposals, enabling consulting from the same perspective as clients facing challenges. I am.
■ Mindset to share ■
When working, we value "sustainability".
It is also a matter of whether or not it is in a reasonable state, but for example, if one job is overwhelmed in terms of time, physical strength, motivation, etc., a good job cannot be done. We can work with a sustainable environment and value standards because we work as a team with the same goals.
■ Working style and working environment ■
More than 100 members including employees, internships, outsiders, and part-time workers are active.
There are many junior members, and the atmosphere is casual and flat.
Currently, we are using remote work, and even those who are hired this time can work with remote work from the beginning. In addition, the insurance and leave system is well-developed, so you can work while maintaining a work-life balance.
We will entrust you with planning and promotion of new business development (joint development with partners) that realizes visualization of corporate SDGs promotion and visualization of CO2 emissions in corporate activities.
In the area of SDGs, where the world's businesses place the highest priority, we receive a large number of inquiries regarding new businesses. We welcome those who can work together on projects to improve the world as well as make the world more convenient with the power of IT!
employee
◎ People from internet business companies
CyberAgent, Rakuten, Recruit HD, LINE, Fringe, Metaps, SHOWROOM, ietty, meleap, Yahoo, GMO, Works Applications, CrowdWorks etc.
◎ Consultant graduates
PwC, Accenture, Deloitte, IBM, NRI, Revamp etc.
◎ People from human resources
Recruit carrier, Persol Career, Pasona, Leverages, JAC etc
◎ Others
ITOCHU, Nomura Securities, Softbank, Nissan Motor etc.
As a world-class science and technology research and development corporation, ICT-leading high-tech companies (AI) that promote future co-creation innovation that promotes research fields (environment / energy, life science, system / information science and technology, nanotechnology / materials, etc.) and SDGs-ESD. , IOT 5G blockchain Quantum computing XR metaverse technology, DX biotechnology and other cutting-edge technologies for research and development, high-quality and original technology development Patented products for sale
Software system development contract development, original software / hardware development. Infrastructure construction, system design / development, strategy planning and market research, IT consulting ERP introduction DX introduction, RPA introduction construction AI & IoT 5G blockchain Quantum computing XR, AR, VR, etc. metaverse technology BIO technology Hardware using cutting-edge technology・ Software development, demonstration experiments, R & D, operation, and sales of prototype products, new energy industry (battery-related) batteries (storage batteries, hydrogen, fuel cells, etc.), battery materials and components, or products that utilize batteries, etc. R & D, prototype development, demonstration experiments, R & D, operation, and sales of prototype products
New energy industry (battery related) BIO technology New energy BIO New materials
Development of components such as lithium-ion batteries and fuel cells
・ Development of storage batteries and hydrogen / fuel cell mobility
・ Development of components and components for hydrogen stations
・ Development of reuse-related technology (storage battery diagnostic device, etc.) for used lithium-ion batteries
・ Development of charging / discharging equipment, manufacturing equipment, and battery management system
・ Development and demonstration experiments of storage batteries, robots that activated fuel cells, drones, and mobility
• AI & IoT5G blockchain IT consulting related to quantum computing, ERP (SAP, salesforce, orcale, etc.) introduction construction and development RPA (WinActor UiPath Automation Anyware Blue Prism Fujitsu RPA) introduction construction and development, AWS, GCP, Azure, etc. cloud Introduction construction and development, EC (shopify, alibabaEC) introduction construction and development / planning / analysis / construction / design / development / support Comprehensive consulting for new introduction / reconstruction Planning design / production, website, printed matter, CI, System planning / design / development / construction SIer and manufacturers provide resident development support. In-house product development Proposal and development of business applications Construction and development of software using multimedia software and general-purpose machines Network construction / server setting, operation management work, system engineering sales support, etc. SIer, resident development support by manufacturers, in-house Product development,
Cutting-edge efforts in the medical / health / nursing field, joint research with NTT, DX initiatives in the medical / nursing field such as telemedicine and utilization of 5G, joint with Sekisui House Co., Ltd.
With "Terumo Corporation", a medical device manufacturer that works on the development of new products through joint research with venture companies, etc., with the keyword "collaboration between different industries" in the healthcare business, which works to create new value such as emergency response services when researching at home. Joint research
• Japan and foreign trade, human resources development industry;
International logistics and import / export business agency, EC (alibaba, taobao, tianmao) International logistics and import / export business agency
Human resources development business, translation business, interpreting business, real estate business, medical health care business;
Partnership with oxford University and Cambridge University in the United Kingdom Partnership with Harvard University, MIT University, etc. AI & IoT research, AI & IoT education EC education,
AI, EC human resource development, academic meetings, academic lectures, seminars, etc., qualification acquisition support system, and technical study sessions using the actual machine environment (Cisco, AI, AWS). Currently, eight study sessions are held every month, and employees participate in popular meetings. It is an environment where you can improve your skills depending on your efforts.
Partnership with alibaba Group EC education, EC construction, introduction and development, information exchange and cooperation with related organizations, etc.
AI solution consulting, EC solution consulting, EC utilization promotion AI utilization promotion
Exchange / cooperation between Japan and foreign countries and globalization
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5G AND INTERNET OF THINGS (IOT)
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ADVERTISING, ENTERTAINMENT & CONTENT
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AUTOMOTIVE
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BLOCKCHAIN
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HEALTH & WELLNESS
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HOME & FAMILY
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IMMERSIVE ENTERTAINMENT
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PRODUCT DESIGN & MANUFACTURING
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ROBOTICS & MACHINE INTELLIGENCE
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SPORTS
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STARTUPS
The purpose of this company is to carry out the following businesses and all businesses incidental to them with the aim of realizing a sustainable society.
(1) Business that contributes to solving all forms of poverty problems everywhere
(2) A business that contributes to solving the problem of hunger, ensuring food stability and improving nutritional status, and promoting sustainable agriculture.
(3) Business that contributes to ensuring healthy lives for all and promoting welfare
(4) A business that contributes to providing inclusive, equitable and high-quality education to all and promoting lifelong learning opportunities.
(5) Business that contributes to empowerment for all gender equality
(6) Business that contributes to ensuring access to water and sanitation and sustainable management for all
(7) A business that contributes to ensuring access to sustainable, modern energy that is affordable, reliable and accessible to all.
(8) Businesses that contribute to the promotion of sustainable, inclusive and sustainable economic growth, productive full employment and Stimulating and creative work for all.
(9) Business that contributes to the development of robust infrastructure, the promotion of inclusive and sustainable industrialization, and the expansion of technological innovation.
(10) Business that contributes to correcting all disparities and eliminating discrimination
(11) Businesses that contribute to making cities and human settlements inclusive, safe, resilient and sustainable
(12) Businesses that contribute to ensuring sustainable consumption and production patterns
(13) Business that contributes to taking emergency measures to prevent climate change and confront its impact
(14) Business that contributes to the sustainable use of the ocean and marine resources for sustainable development.
(15) Contribute to the protection of terrestrial ecosystems, promotion of restoration and sustainable use, sustainable management of forests, coping with desertification, prevention and reversal of land degradation, and prevention of biodiversity loss. business
(16) To promote a peaceful and inclusive society for sustainable development, to provide access to justice for all, and to build effective and responsible inclusive institutions at all levels. Business that contributes
(17) Business that contributes to revitalizing global partnerships by strengthening implementation measures for sustainable development
Our company aims to carry out the following business.
(1) Manufacture and sale of R & D products for the following items
(1) Global warming mitigation products, decarbonized products, SDGs compliant products, measures to realize a sound material-cycle society, renewable energy
② Energy management system
③ Life science, medical health, long-term care welfare technology
④ Humanities and Social Sciences
⑤ Life science / clinical medicine
⑥ Digital utilization support promotion business
⑦ Social Systems Science
⑧ Security trust field
⑨ Material / device field
⑩ Materials Informatics (Nanotechnology / Materials field)
⑪ Bio-life / healthcare field
⑫ Environment / energy field
⑬ Department of Biotechnology
⑭ Department of Environmental Energy Engineering
⑮ IoT edge computing technology
⑯ Department of Bio-Information Engineering
⑰ Department of Information Systems Engineering
⑱ Graduate School of Human Sciences (Department of Physical Sciences, Department of Environmental Energy, Department of Electrical and Electronic Information Engineering), Graduate School of Information Science (Department of Bioinformatics, Department of Information Systems Engineering), Graduate School of Basic Sciences (Material Creation) Department of Science), Center for International Exchange of Sciences, Institute of Proteins, Institute of Industrial Science, Graduate School of Human Sciences, Graduate School of Language and Culture, Global Initiative Organization, Graduate School of International Public Policy
⑲ Infectious disease problem and environment / energy field
⑳ Information / system field
21 Machine learning / deep learning technology (system / information field)
22 Data-based problem solving (system / information field)
23 Service Science (System / Information)
24 Climate change observation (environment / energy field)
25 Climate Change Forecast (Environment / Energy Field)
26 Fracture mechanics (environment / energy field)
27 Development of high-efficiency CO2 separation and recovery / carbon cycle technology from the atmosphere
28 Research and development of bioprocesses that use electrical energy to fix atmospheric CO2
29 Development of an innovative CO2 mass resource recovery system centered on electrochemical processes
30 Reduction of greenhouse gas emissions from agricultural land by optimizing resource recycling
31 Research and development of CO2 circulation system for the realization of “Beyond Zero” society
32 Research and development of multi-lock biopolymers that can be decomposed into the ocean using non-edible biomass as a raw material
33 Research and development of biodegradable plastics with biodegradation start switch function
34 Development and research of optical switch type marine degradable edible plastic
35 Bioeconomic culture food production system by circular cell culture using algae and animal cells
36 Research on food loss reduction and associated environmental load reduction throughout the food chain
37 Construction of a recycling-type cooperative agricultural platform by environmental control based on soil microflora atlas
38 Realization of zero pest damage agriculture by making full use of advanced physical methods and unused biological functions
39 Feeding and feeding of unused wood using the destructive wood decomposition capacity of termites
40 Development of a circulating food production system supported by insects to solve global food problems and advance humankind into space
41 Development of innovative food solutions that reduce food loss and improve QoL at the same time
㉑ Robotics
㉒ Brain science
㉓ "" Clean Call "Clean Call Technology Promotion Business"
㉔ Coal gas screen-up technology for fuel cells
㉕ Zero Emission Coal-Fired Technology Development Technology for Zero Emission
㉗ Next-generation gasification system technology development
㉘ Zero-emission coal-fired basic technology development
㉙ Zero Emission Coal-Fired Total System
㉚ CO2 separation and recovery technology
㉛ Satellite exploration technology / hyperspectral sensor
㉜ Deep learning technology
㉝ Utilization of chemical energy (environment / energy field)
㉞ Separation technology (nanotechnology / materials field)
42 Water cycle (water resources / water disaster prevention) (environment / energy field)
43 Digital Transformation CPS (Cyber Physical System)
44 Nanotechnology / Materials
45 Computing architecture
46 Digital transformation
47 Artificial Intelligence (AI) / Big Data
48 blockchain
49 5th generation mobile communication system
Internet of Things 50
51 Sensor
52 Internet of Things devices
53 Augmented reality, virtual reality, mixed reality
54 Cross Reality
55 Metaverse Business
56 New materials by nanotechnology
57 Material creation technology
58 Creation / separation / circulation of high-performance materials
59 Control of formation / decomposition of composite structure aiming at material cycle ~ Sustainable element (Science of formation / decomposition of composite structure)
60 Disease prevention and health promotion, creation of new treatment strategies for diseases-Biosensory system-Creation of basic technology for integrated understanding and control from acceptance-
61 Development of basic technology for controlling biosensory systems
62 Principle of phytochemical production and research and development for its utilization-highly applied research and development such as biopharmacy production by plants
63 New materials by biotechnology
64 Quantum communication and quantum computer
65 AI x Bio DX Era Life Science Biomedical
66 Research Transformation (RX)
67 Designer Cell Regeneration / Cell Medicine / Gene Therapy
68 Creation of next-generation breeding and biological production infrastructure Creation of infrastructure to realize agriculture with reduced environmental load under climate change-Toward the development of a model that handles microorganisms, crops, and weather in the field in an integrated manner-
(2) New business creation, new product R & D, prototype development, demonstration experiment, R & D / operation / sales of prototype products and manufacturing / sales of R & D products
(1) Recycling-type economy / decarbonization / sustainable development goals SDGs realization / environment (Environment) "" Society "" Governance (Governance) ESD management model, warming climate change countermeasures / renewable energy
(2) Energy resource exploration / development technology, CCS, thermal power generation, nuclear power generation, solar power generation, wind power generation, biomass power generation / utilization, other renewable energy power generation (hydraulic, ocean, geothermal, solar heat), electric energy utilization (energy management) System), electrical energy utilization (power storage), thermal energy utilization (industrial heat utilization), thermal energy utilization (commercial heat utilization), chemical energy utilization, district heat supply (district heating and cooling), energy system evaluation, reactive thermal fluid, Tribology, destructive mechanics, computational engineering
③ Climate change observation, climate change prediction, water cycle (water resources / water disaster prevention), water utilization / water treatment, removal / purification technology (air, soil / groundwater), organic chemical substance analysis / toxicity evaluation, inorganic chemical substance analysis / dynamics Understanding, observation / evaluation / prediction of ecosystem / biodiversity, evaluation / prediction of society-ecosystem, recycling and life cycle evaluation, urban environmental sustainability (climate change adaptation, infectious diseases, health), climate in agriculture, forestry and fisheries Adaptation / mitigation of fluctuations
④ Hydrogen / fuel cell field
⑤ Smart grid field
⑥ Storage / energy
⑦ Resource recycling / waste treatment / recycling technology and bioplastic technology
⑧ Resource recycling / energy source for biomass resources
⑨ Atmospheric environment
⑩ Water / soil environment
⑪ Urban global environment
⑫ Next-generation energy
① Health / medical / long-term care industry
-1 New biopharmacy (vaccines, proteins, nucleic acids, etc.)
-2 Regenerative medicine (iPS cells, etc.)
-3 Personalized medicine (gene diagnosis, gene therapy)
-4 Diagnostic equipment / medical equipment
-5 Fusion of medical / nursing robot / IT and engineering with prevention and diagnostic treatment
② Food, agriculture, forestry and fisheries, agriculture
1 Agricultural technology
2 Food manufacturing technology, health food manufacturing and sales business
3 Digital transformation of food itself
4 Food metabolomics
5 Plant genome editing
Regarding "6 Bio-Production", in addition to further improving the technology for producing micro-materials, we will develop practical technologies for the production of biologic drugs such as antibodies and vaccines and the production of iPS cells.
7 High-efficiency production technology (genetically modified crops, trees, etc.)
8 Health foods, plant factories, aquaculture technology (various fish, eels, etc.)
③ Environment / life business
(1) Measures against marine plastics, recycling of plastic resources, and environmentally regenerated products
② Sustainable use of plastic Bioplastic technology
③ Regional food resource recycling solution (bio-carbonized type) Bio-carbon that produces bio-charcoal from various organic resources
④ Manufacture and sales of plastic products
⑤ Planning, design, manufacturing and sales of apparel products
⑥ Apparel industry Contributes to environmental conservation with sustainable materials and renewable energy Product planning, design, manufacturing and sales
⑦ Conversion from recycling to repair in the apparel industry Reuse of waste as raw materials and energy
⑧ Realization of a sustainable sound material-cycle society Planning, design, manufacturing and sales of bioplastics, paper products, recycled products, etc. that contribute to the environment
④ Manufacturing technology
⑤ Production operation stage (environmental protection technology)
⑥ New material technology
⑦ Transportation technology
⑧ Biotechnology
⑨ Energy industry (battery-related) Batteries (batteries, hydrogen, fuel cells, etc.), battery materials, components, etc., renewable bioenergy (bioethanol, etc.)
⑩ Next-generation battery development and manufacturing support
⑪ Fuel cell system
⑫ Biochemical (produces chemical products from bioethanol, etc.)
⑬ Useful enzymes (production of rare natural products by bioreactor, new enzyme agents, etc.)
⑭ Environmental purification technology (environmental purification using microorganisms and plants, accumulation of rare elements, etc.), etc.
⑮ Next-generation information and communication technology
⑯ Next-generation vehicle EV (electric vehicle) and FCV (fuel cell vehicle)
⑰ FCV (hydrogen vehicle)
(3) Information and communication industry
(1) Software system development Contract development, original software / hardware development. Infrastructure construction, system design / development, strategy planning and market research
(2) Information technology consulting, enterprise resource planning ERP introduction, digital transformation introduction, robotic process automation RPA introduction construction, etc.
③ Planning, production, sales of computer software, information processing service for computers
Screw industry, software development, trading and information service industry
④ Planning, production and sales of audio and video software
⑤ Planning, development, sales, contracting and consulting of applications using the Internet
(4) Worker dispatching business
(5) Paid employment agency business
(6) Management consulting business
(7) Management of foreign language classes
(8) Translation, publishing and interpretation of foreign documents
(9) Real estate industry
(10) Trade industry
(11) Publishing and printing
(12) Advertising agency business, insurance agency business, broadcasting business, travel tourism / sports leisure business and other service businesses
(13) Financial industry
(14) Advice, guidance and assistance regarding business support and management
(15) Business related to investment in stocks, bonds, etc.
(16) Medical, welfare and long-term care consulting
(17) Financial planning business
(18) Warming / Energy Natural Environment / Biodiversity Resource Recycling / Waste Chemical Substances Soil / Groundwater Water Quality Atmosphere Environmental Accounting / Environmental Management Next-Generation Vehicles
AI processing x quantum computing technology Powerful computing power x Beyond 5G communication service
Brain-type AI x quantum ICT, security technology, etc. ・ Quantum cryptographic communication
With Beyond 5G communication service
Global warming mitigation products, decarbonized products, SDGs compliant products, measures to realize a sound material-cycle society, renewable energy
With Beyond 5G communication service
Used in Metaverse area NFT
Quantum life technology (quantum bio) (eg, biological nano-quantum sensor, quantum entangled optical imaging, hyperpolarized nuclear magnetic resonance technology (hyperpolarized / ultrasmall MRI), etc.)
・ Quantum security technology (eg quantum secure cloud, optical / quantum network encryption, etc.)
What kind of service is HOCITGROUP NFT? We asked Kokuryu, CTO of the NFT Division of the Advanced Technology Research Group, who is the president of HOCITGROUP. Focusing on the six fields of sports, idols, manga / animation, games, art, and SDGS x scientific research and development, IP (intellectual property) holders can issue NFTs and build sales sites for companies, as well as users. We provide consumer services that allow individuals to buy and sell purchased NFT products.












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1. Planning promotion business
It is made up of teams with influential influencers and Vtubers at home and abroad, as well as successful achievements and know-how. We support the promotion of businesses by researching new technologies, new services created by them, and forms of public relations.
2. Metaverse product development / NFT product development business
Together with a technical team with a proven track record in the area of Metaverse, we are jointly researching and developing a Metaverse system that can be used for various purposes such as live performances, concerts, and exhibitions. (Scheduled to be released in the first quarter of 2022)
By using this product, it is possible to implement a sales promotion tie-up with apparel and brands, and a monetization mechanism that combines live commerce and NFT. This opens up new possibilities for IP targeting fan marketing and the global market.
3. New business development business
We are developing new businesses by utilizing the unique Metaverse technology and NFT knowledge provided by Metaheroes, the comprehensive marketing support system, and the domestic and overseas industry networks.
In the future, in the new generation after the appearance of Metaverse, various businesses will be born and we will build a mechanism to discharge heroes who contribute to society.
NFT(Non-Fungible Token)
No-code AI is a category in the AI landscape that aims to democratize AI. No-code AI means using a no-code development platform with a visual, code-free, and often drag-and-drop interface to deploy AI and machine learning models. No code AI enables non-technical users to quickly classify, analyze data and easily build accurate models to make predictions. Businesses need to build AI models. No-code AI solutions have not yet replaced data scientists. This is still an emerging field. Increasing the maturity and flexibility of existing solutions and widespread integrations will drive more adoption. No-code AI reduces the time to build AI models to minutes enabling companies to easily adopt machine learning models in their processes. Thanks to no-code solutions, business users can leverage their domain-specific experience and quickly build AI solutions. One of the most obvious benefits of automation and no code technologies is savings. Companies need fewer data scientists when they can have their business users build machine learning models. For businesses that already have a data science team, requests of other employees shift the team’s focus to easy-to-solve tasks. No-code solutions minimize these distracting requests since they enable business users to tackle such requests themselves.These categories may merge into one category that enables non-technical employees to quickly develop AI solutions. However, currently, the categories are slightly different:AutoML solutions are focused on empowering data scientists to be more efficient. They provide transparency on the whole machine learning pipeline which increases complexity but also allows data scientists to refine how models are built.No code AI solutions are focused on helping non-technical users build ML models without getting into the details of every step in the process of building an ML model. This makes them easy to use but harder to customize. No-code vendors are positioned in the market based on their technology such as NLP, computer vision, voice recognition, analytics.




