Social and location recommendations are hot research topics as filtered suggestions are highly desirable to cope with information explosion problems when data being generated by mobile and socially connected users grow at a rapid pace. In this keynote, I plan to present some of our recent work in social and Location recommendation based on a matrix factorization framework. I will outline novel ways on how we can use social ensemble, trust relations, tags, click-through-rate, etc. to improve social and location recommender systems for a wide-range of applications and services.

Prof. Irwin King's research interests include social computing, machine learning, big data, web intelligence, and multimedia processing. In these research areas, he has over 200 technical publications in journals, conferences, book chapters, and edited volumes. He was the General Chair of Web Search and Data Mining (WSDM2011), ACM Recommender Systesms (RecSys2013), and also has been involved with the organization and/or technical program of many international conferences such as WWW, SIGIR, KDD, AAAI, etc. Moreover, he has served as reviewer and panel member for Research Grants Council (RGC) of Hong Kong, Natural Sciences and Engineering Research Council of Canada (NSERC), National Natural Science Foundation of China (NSFC), and Natural Science, and Engineering of Academy of Finland. Dr. King is an Associate Editor of ACM Transactions on Knowledge Discovery from Data (ACM TKDD), Neural Networks Journal, and a former Associate Editor of the IEEE Transactions on Neural Networks (TNN). He is a member of the Editorial Board and Special Issue Editor of a number of international journals. He is Professor at the Department of Computer Science and Engineering, The Chinese University of Hong Kong. Recently, he was on leave with AT&T Labs Research, San Francisco and was also teaching Social Computing and Data Mining as a Visiting Professor at UC Berkeley. He received his B.Sc. degree in Engineering and Applied Science from California Institute of Technology, Pasadena and both his M.Sc. and Ph.D. degrees in Computer Science from the University of Southern California, Los Angeles. See http://irwinking.com for more information.

1. POI Recommendation in Location-based Social Networks