报 告 人：Ridha Khedri[加拿大McMaster University, 国家高端外国专家]
报告时间：2016年9月 9日（周五）10: 0～11: 30
邀 请 人：陈怡海 博士
With the growing interest in Big Data and Internet of things, new approaches are needed to reason on the massive amounts of data collected and to generate useful information from it. It is essential to have a systematic approach to generate the concepts of the domain of application directly from a data set. These concepts will enable the reasoning process to extract valuable information from data. The concepts of the domain of application are usually structured into an ontology, which is commonly used to provide explicit specifications of a conceptualization of a domain. Ontologies have been used for the representation of knowledge in many areas. To reason on Big Data, traditional ontology-based reasoning approaches are inadequate due to the structure and the content of the used ontologies. The talk presents a system to capture domain knowledge that overcomes the shortcomings of traditional ontologies. The system can be separated into three distinct components. The first component is the structure of concepts and their relationships. We refer to it as abstract ontology. The second component serves for modeling the data stored in the information system. The third component consists of the algebraic specifications that give more links between the two previous components of the domain information system. The work to be presented in the talk aims at expanding our current understanding of ontologies to give them better structure in order to support reasoning on Big Data. Our results encompass the main ideas in the area and reconcile some of them. We conjecture that it will enable us to scale up reasoning on data sets to an unprecedented large sizes and to generate from them more telling information on the domain of application.
Keywords: Artificial Intelligence, Big Data, Automated Reasoning, Ontologies
Ridha Khedri is a Professor of software engineering at McMaster University, where he is the Chair of the department of Computing and Software. He is Adjunct Professor in the School of Computer Engineering and Science, Shanghai University. He received a M.Sc. and a Ph.D. from Laval University, Quebec, Canada, in 1993 and 1998 respectively. In March 1998, he joined the Communications Research Laboratories of McMaster University as a post-doctoral researcher under the supervision of Prof. David L. Parnas. From December 1998 to June 2005 he was an Assistant Professor at McMaster University. From July 2005 to June 2014 he was an Associate Professor at McMaster University. His research interests include algebraic methods in software engineering, analysis of information security policies and of cryptographic-key distribution scheme, data cleaning, software product families, and formal software requirements analysis. He organized or served on the program committee of more than 30 conferences and workshops. He is a licensed professional engineer in the province of Ontario. He is a member of the Association for Computing Machinery and the IEEE Computer Society.