Research
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Recommender Systems: User Experience and System Issues |
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Joseph A. Konstan Department of Computer Science and Engineering University of Minnesota |
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Over the past decade, recommender systems employing collaborative filtering technology have evolved from research proofs-of-concept to commonplace components of e-commerce web sites and direct marketing. At the same time, research has moved forward to embrace more sophisticated algorithms and more detailed exploration of the user experience. This talk reviews recent highlights from the decade-old GroupLens Research Project, including an exploration of techniques for getting new users started in recommender systems, building recommender systems for groups of users, user interface design issues, using citation webs to recommend research papers, and recent advances in algorithm design.
Joseph A. Konstan is Associate Professor of Computer Science and Engineering at the University of Minnesota. His research addresses a variety of human-computer interaction issues related to filtering, comprehending, organizing, and automating large and complex data sets. He is probably best known for his work in collaborative filtering (the GroupLens project). He is co-author of Word of Mouse: The Marketing Power of Collaborative Filtering, a book that reviews three dozen good and poor examples of personalization in research and deployed systems.
Dr. Konstan received his Ph.D. from the University of California, Berkeley in 1993. He is an ACM Distinguished Lecturer and IEEE Distinguished Visitor. He serves as Chair of ACM SIGCHI, the professional society for Human-Computer Interaction.
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