Designing Better Recommendation Systems: Learning from Context ...

Designing Better Recommendation Systems: Learning from Context to Enhance Personalization

Intelligent personalized services such as recommender systems help alleviate information overload by tailoring their output to users' personal preferences. Most intelligent personalized tools, however, do not take into account the fact that users interact with systems in a particular context. Context-aware recommender systems, on the other hand, adjust their recommendations to be both personalized and suitable for the current circumstances of users. In this talk, Dr. Mobasher will explore context adaptation where context is discovered both implicitly from users’ behavioral cues as well as explicitly from pre-defined variables such as time, location, and device. He will present several effective techniques for designing adaptive systems that learn user preferences over time and integrate user context into the modeling and prediction processes.

About Bamshad Mobasher

Dr. Bamshad Mobasher is a professor of Computer Science and the director of the Center for Web Intelligence at DePaul University College of Computing and Digital Media in Chicago. He is also the co-founder and the director of the Center for Data Mining and Predictive Analytics at DePaul University. His general research areas include artificial intelligence and data mining. In particular, he is considered one of the leading authorities in Web mining, Web personalization, and recommender systems. He has published 5 edited books and approximately 200 scientific articles in these areas. As the director of the Center for Web Intelligence, he directs research focusing on creating more intelligent, personalized Web applications; and he works with the industry on numerous joint projects. He serves in leadership positions of several international conferences, including the ACM Conference on Recommender Systems, ACM SIGKDD Conference on Knowledge Discovery and Data Mining, and the International Conference on User Modeling, Adaptation, and Personalization. Dr. Mobasher serves as an associate editor for the ACM Transactions on the Web, the ACM Transactions on Internet Technology and the ACM Transactions on Intelligent Interactive Systems. He has also served on the editorial boards of several other prominent computing journals.