Recommender Systems

Tuesday, March 22, 2016 - 1:25pm - 2:25pm
George Karypis (University of Minnesota, Twin Cities)
Recommender systems are designed to identify the items that a user will like or find useful based on the user’s prior preferences and activities. These systems have become ubiquitous and are an essential tool for information filtering and (e-)commerce. Over the years, collaborative filtering, which derive these recommendations by leveraging past activities of groups of users, has emerged as the most prominent approach for solving this problem.
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