What’s Special about Mobile Recommender Systems?

Title: What’s Special about Mobile Recommender Systems?

Speaker: Prof. Hui Xiong

Time: May 7th

Venue: FIT 1-315

Abstract. Recommender systems aim to identify content of interest from overloaded information by exploiting the opinions of a community of users. Developing personalized recommender systems in mobile and pervasive environments is more challenging than developing recommender systems from traditional domains due to the complexity of spatial data, the unclear roles of context-aware information, and the increasing availability of environment-sensing capabilities. In this talk, we introduce the unique features that distinguish pervasive personalized recommendation systems from classic recommendation systems. An examination of major research needs in pervasive personalized recommendation research reveals some new opportunities for personalized recommendation in mobile and pervasive applications.

Short-Biography

Dr. Hui Xiong is currently an Associate Professor and the Vice Chair of the Management Science and Information Systems Department at the Rutgers, the State University of New Jersey, where he received a two-year early promotion/tenure (2009), the Rutgers University Board of Trustees Research Fellowship for Scholarly Excellence (2009), the ICDM-2011 Best Research Paper Award (2011), the Junior Faculty Teaching Excellence Award (2007) and the Junior Faculty Research Award (2008) at Rutgers Business School. Dr. Xiong received his Ph.D. in Computer Science from the University of Minnesota (UMN), USA, in 2005, the B.E. degree in Automation from the University of Science and Technology of China (USTC), Hefei, China, and the M.S. degree in Computer Science from the National University of Singapore (NUS), Singapore. His general area of research is data and knowledge engineering, with a focus on developing effective and efficient data analysis techniques for emerging data intensive applications. He has published prolifically in refereed journals and conference proceedings (3 books, 40+ journal papers, and 60+ conference papers). He is the co-Editor-in-Chief of Encyclopedia of GIS (Springer, 2007) and an Associate Editor of the Knowledge and Information Systems journal. He has served regularly on the organization and program committees of numerous conferences, including as a Program Co-Chair of the Industrial and Government Track for the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD). He is a senior member of the ACM and the IEEE.