• 2021-04-21 Wednesday

Sponsored by the Chinese Association for Artificial Intelligence (CAAI) and organized by the School of Computer Science and Technology of Fudan University and CAAI Intelligence Service Committee, CAAI Intelligence Service Committee online forum -- the Scientific and Technological Big Data and Services, and the establishment of Scientific and Technological Big Data Professional Group of CAAI Intelligence Service Committee will be held online from 19:00 to 21:00 on February 2nd, 2021.

How to participate?

Live time: 19:00-21:00, February 2, 2021

Participation mode: Scan the QR code below to watch the live

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Brief introduction

Report 1: Research on Intelligent Talent Mining and Service Based on Big Data

Speaker: Professor Li Juanzi

Abstract:Mining the rules of knowledge innovation and dissemination from massive big data can speed up scientific and technological innovation and promote technological progress, which has always been the international academic hot spot. This report will introduce the key technologies of mining and serving intelligent talents, with the goal of scientific and technological innovation.

Personal profile: Li Juanzi, Ph.D., Professor of Tsinghua University, director of Knowledge Intelligence Center of Institute of Artificial Intelligence of Tsinghua University, director of Language and Knowledge Computing committee of Chinese Information Society of China. His research direction is knowledge engineering, knowledge mapping and news mining. In recent years, more than 100 papers of his have been published in important international conferences and academic journals, and his works have been cited more than 8000 times in Google.

He edited and published Mining User Generated Content and Semantic Mining in Social Networks. He won the first prize of Beijing Science and Technology Progress Award in 2017, the first prize of CAAI Science and Technology Progress Award in 2013, and the first prize of WangXuan News Science and Technology Progress Award in 2011.

Report 2: Evaluation of Science and Technology Big Data

Speaker: Professor Liu Yezheng

Abstract:Based on the value chain of science and technology big data, Liu introduced the main evaluation strategies of different value-added activities, takes the big data of scientific papers as an example, introduces its value evaluation methods. Liu puts forward the future research prospects based on the situation that different types of science and technology big data have different value evaluation standards because of the variety of science and technology big data.

Personal profile: Liu Yezheng, Professor of School of Management, Hefei University of Technology, national candidate of "New Century Talent Project", member of Expert Committee of National Engineering Laboratory of Big Data Circulation and Transaction Technology, and director of Cross Cloud Data Fusion Analysis Research Technology Center. He has undertaken major projects of National Natural Science Foundation of China, key funded projects of national major research programs, national key research and development program, National 973 Program, and enterprise cooperation program of Baidu, Alibaba, Jingdong, Chery Automobile, etc.

He has won two first prizes and two second prizes of provincial and ministerial level scientific and technological progress award, published two academic monographs in Science Press, and published more than 100 papers in domestic and foreign academic journals and international academic conferences such as Marketing Science, IEEE TKDE, EJOR, Journal of Management Science, Management World, etc. His main research fields include e-commerce and cyberspace management, big data analysis and decision science, organizational behavior under social technology system.

Report 3: Research on Group Behavior Based on Big Data

Reporter: Researcher Shen Huawei

Abstract:The increasingly rich science and technology big data provides us with valuable basic data resources for the analysis and understanding of academic evaluation, innovation communication and academic behavior. The speaker will introduce his research on group behavior based on big data of scientific citation, mainly including two aspects of group credit allocation and group attention prediction. In terms of group credit distribution, Shen will introduce the mechanism of credit distribution among team members in academic cooperation. In terms of group attention prediction, he will introduce how to model the process of academic achievements to obtain group attention, so as to predict the long-term impact of academic achievements.

Personal profile: Shen Huawei, researcher of Institute of Computing Technology, Chinese Academy of Sciences, Professor of University of Chinese Academy of Sciences, young scientist of Beijing Zhiyuan Institute of Artificial Intelligence, and deputy director of Social Media Processing Committee of Chinese Information Society. The main research fields are social media computing, network data mining, graph neural network.  He has published more than 100 papers in journals such as PNAS, IEEE TKDE and international conferences such as WWW, SIGIR and ICLR, and 4 papers have won the best paper award. He won the second prize of National Technological Invention Award, the Special Award of President of Chinese Academy of Sciences, Hanwang Youth Innovation Award, and first prize of Qian Weichang Chinese Information Processing Science and Technology. He was selected as an outstanding member of the Youth Innovation Promotion Association of Chinese Academy of Sciences and Wang Kuancheng First Talent Plan of Chinese Academy of Sciences.

Report 4: Construction of Smart Knowledge Service Ecology Based on Big Data

Reporter: Researcher Qian Li

Abstract:Big data has both the common characteristics of big data and its own characteristics. Under the policy environment of innovation driven development strategy, the construction, analysis, mining and application ecology of big data are particularly important. This report focuses on the construction of scientific and technological big data knowledge resource system, introduces the design of scientific and technological big data model, data acquisition and integration, research and development of big data intelligent engine and construction of academic knowledge map, and finally introduces the construction practice of intelligent knowledge service ecosystem for scientific research and decision-making.

Personal profile: Qian Li, Ph.D., researcher, master's supervisor, is director of Information System Department of Literature and Information Center of Chinese Academy of Sciences and leader of Knowledge Service Platform Construction Coordination Group, deputy director of data research and management center of national science and Technology Library and Literature Center (NSTL), member of Youth Innovation Promotion Association of Chinese Academy of Sciences, and Young Information Scientist of 2019.

He is a post teacher in the Department of Library, Information and Archives Management of the University of Chinese Academy of Sciences, teaching "Data Analysis Technology of Scientific and Technological Information". He is engaged in the research of Knowledge Computing and intelligence knowledge service methods for scientific and technological big data. His main research fields include scientific and technological big data, knowledge computing, research and design, fingerprint identification, text semantic mining, etc.

He is undertaking many major research projects of the Ministry of Science and Technology, JW Science and Technology Commission and Chinese Academy of Sciences. He has published more than 50 academic papers, 1 monograph and 5 patents. He led his team to build an intelligent knowledge service platform called "Smart Scientific Research"( https://scholarin.cn/ ), which has become the next generation of open science and technology knowledge service ecology integrating "knowledge acquisition, talent discovery, technology identification, achievement transformation, industry consultation and decision support".

Report 5: Construction of Large Scale Scientific and Technological Knowledge Map and Its Application In The Field of Scientific and Technological Information

Reporter: Associate researcher Wang Deqing

Abstract:As an indispensable resource in the field of artificial intelligence, data is paid more and more attention by researchers. The data resources in the field of science and technology are mainly based on scientific research achievements (papers, patents, projects, standards, awards, etc.), which are the crystallization of the wisdom of scientific researchers.

There are more than 200 million scientific and technological documents in the world, and up to 5 million academic papers are published every year.

This report introduces the corresponding big data processing and analysis technology based on the integration of large-scale big data and the construction of large-scale scientific and technological knowledge map. At the same time, taking the application of science and technology information field based on knowledge mapping as a service case, Wang will introduce the real application scenarios of data intelligence service, realizes data-driven intelligent services such as automatic discovery of science and technology hotspots, automatic analysis of science and technology trends and intelligent decision-making of science and technology, which strongly supports the decision-making of science and technology management departments in China.

Personal profile: Dr. Wang Deqing, associate researcher and doctoral supervisor of School of Computer Science, Beihang University since 2015, chief engineer of National Science and Technology Resource Sharing Service Technology Research Center, member of CCF Big Data Expert Committee. Visiting scholar at New Jersey State University (Rutgers University) from November 2016 to November 2017. The main research directions are knowledge mapping, machine learning and scientific research big data analysis and mining.

As the project leader, he undertook 1 key project of national defense innovation zone, 2 key R & D projects, 1 youth fund, 5 provincial and ministerial projects, and 10 enterprise projects. He is also in charge of research and development of Zhitu app (IOS, Android Market), Technology Search 2.0( kejso.com ), Standard Big Data Platform( bigdata.cssn.net. cn) have been put into operation and achieved good results. He has published 15 SCI papers in top journals such as Big Data Analysis and Data Mining, 18 EI papers in well-known international academic conferences and core journals such as AAAI and IJCAI, 3 authorized patents, 2 national standards and 3 software copyrights.




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