来源： 计算机学院 | 发表时间： 2019-09-09 | 浏览次数： 10
报告题目：Semantic Link Network in Cyber-Physical Society
报 告 人：诸葛海
An approach to modelling reality is constructing a relational system consisting of a base relational network and a superstructure that determines the semantics, motivation, strategies, and principles of operating and evolving the system. Semantic Link Network connects versatile individuals and guides various flows (including material flow, data flow, information flow and knowledge flow) in cyberspace, physical space and social space, forming and evolving Semantic Link Network that renders Cyber-Physical-Social Intelligence.
Hai Zhuge is a Distinguished Scientist of the ACM and a Fellow of British Computer Society. He has made a systematic contribution to semantics and knowledge modeling through lasting fundamental research on the Semantic Link Network and the Resource Space Model based on multi-dimensional methodology. He is leading research toward Cyber--Physical Society through methodological, theoretical and technical innovation. He gave 17 keynotes at international conferences and invited lectures in universities of many countries as a Distinguished Speaker of the ACM. As a chair in computer science, he leads the International Research Network on Cyber–Physical–Social Intelligence consisting of Aston University, Guangzhou University, KLIIP at Institute of Computing Technology in Chinese Academy of Sciences, and University of Chinese Academy of Sciences. He was a Distinguished Visiting Fellow of Royal Academy of Engineering. He is the author of four monographs: Cyber–Physical–Social Intelligence on Human–Machine–Nature Symbiosis (Springer, 2019), Multi-Dimensional Summarization in Cyber–Physical Society (Morgan Kaufmann, 2016), The Knowledge Grid: Toward Cyber–Physical Society (World Scientific, 2012, 2nd edition), and The Web Resource Space Model (Springer, 2008). He was an associate editor of the Future Generation Computer Systems. He is serving as an associate editor of the IEEE Intelligent Systems. Homepage: http://www.knowledgegrid.net/~h.zhuge.