报告题目：SemRec: A Semantic Enhancement Framework for Tag based Recommendation
报告时间：2011年9月23日上午9点
报告地点：电三楼六楼计算机学院学术报告厅
报告摘要：Collaborative tagging services provided by various social web sites become popular means to mark web resources for different purposes such as categorization, expression of a preference and so on. However, the tags are of syntactic nature, in a free style and do not reflect semantics, resulting in the problems of redundancy, ambiguity and less semantics. Current tag-based recommender systems mainly take the explicit structural information among users, resources and tags into consideration, while neglecting the important implicit semantic relationships hidden in tagging data. In this study, we propose a Semantic Enhancement Recommendation strategy (SemRec), based on both structural information and semantic information through a unified fusion model. Extensive experiments conducted on two real datasets demonstrate the effectiveness of our approaches.
报告人简介：
Dr. Guandong Xu has received his PhD degree in Computer Science from Victoria University, Australia in 2008. He is now working as a Research Fellow in the Centre for Applied Informatics at Victoria University, Australia. His research interests cover Data management and Analytics, Data Mining, Machine Learning; Information retrieval and processing, Web search; Intelligent Web Systems, Web mining, Web Communities, as well as Social Informatics and Health Informatics. He has extensively published 40+ papers in referred international journals and conferences proceedings including the Computer Journal, Knowledge-based Systems, Concurrency and Computation: Practice and Experience, Web Intelligence and Agent Systems: an International Journal, Expert System with Applications, Information Processing Letter; and AAAI, CIKM, WISE, IJCNN,KES, WI, ADMA conferences etc. He has authored or is writing (editing) three scientific books with Springer and IGI publisher.
举办单位：计算机学院、研究生院