2. Recommender Systems in E-Commerce: How Collaborative Filtering is Helping Businesses Serve Customers Better

Instructors: Joe Konstan and John Riedl, University of Minnesota

Email:riedl@cs.umn.edu, konstan@mail.cs.umn.edu

Description on tutorial for brochure/site:

A completely updated tutorial on collaborative filtering. After taking this tutorial, students will be ready to: (1) Design new recommender system applications; and (2) Use recommender systems in their research. The tutorial will cover:

- history of recommender systems
- elements of recommender systems
- techniques and algorithms for recommendation
- applications of recommender systems in E-commerce
- review of existing use of recommender systems in practice: winners, losers, and weirdos
- state of the art and forthcoming research on recommender systems from the fields of CSCW, AI, Machine Learning, and Information Retrieval

Intended audience:

Practitioners and researchers interested in real-time personalization. The attendee will become familiar with the state-of-the-art in recommender systems, and will learn which approaches are successful in practice and which research ideas are most promising.

About the instructors:

Joe Konstan and John Riedl direct the GroupLens Research group at the University of Minnesota, which has been researching recommender systems since 1992. They are co-founders of Net Perceptions, the leading vendor of recommender systems. They are both associate professors of computer science and engineering at the University of Minneosta. Both Konstan and Riedl are award-winning teachers with experience teaching conference tutorials and professional short courses.