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.

Physical and Mathematical Sciences

Biological Sciences

Engineering and Applied Sciences

Biomedical Sciences

Behavioral and Social Sciences

Applied Biological, Agricultural, and Environmental Sciences

National Academy of Sciences

Japan Academy

Royal Society

Prussian Academy of Sciences

French Academy of Sciences

Royal Swedish Academy of Sciences

Russian Academy of Sciences

Royal Netherlands Academy of Arts and Sciences

External link

SCIENCES

Nature

National Science Foundation

NASA NSAS

• National Medal of Science

• Alan T. Waterman Award

• Vannevar Bush Award

National Science Foundation
AAAS　American Association for the Advancement of Science

Andrew Zisserman research Lab

Visiting Professor of Tsinghua University

1-308, FIT Building, Tsinghua University, Beijing, 100084. China PR.

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 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.

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]
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]
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]
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]
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]
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]
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*]
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]
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*]
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]
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]
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]
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]
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]
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*]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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)]
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]
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]
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]
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]
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]
GuoLong,Jie Tang and Juanzi Li. Semantic Mining of Social Networks. Morgan & Claypool Publishers, 2015. [DRAFT]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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]
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)
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]
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]
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]
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]
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]
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]
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]
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)
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]
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]
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]
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]
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]
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]
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)
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]
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)
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]
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)
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]
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]
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]
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]
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)
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]
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...)
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]
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]
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...)
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...)
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

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]
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]
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]
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...)
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]
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]
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]
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]
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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