Binary Collaborative Filtering by One-class Classifiers
نویسندگان
چکیده
Contact Information: Marcel J. T. Reinders, Jun Wang Short Description: Collaborative filtering (CF) is any algorithm that filters information for a user based on a collection of user profiles. Since users having similar profiles may share similar interests. For a user, information can be filtered in/out regarding to his similar users' behaviors. User profiles can be either explicitly obtained by user rating or implicitly learned from the recorded user interaction data (i.e. user play-lists). In literature, explicit rating based CF has been widely studied while binary CF (using user interaction data) has only partially investigated. Moreover, most of the binary CF algorithms treat the items that users did not yet play/watch as the “un-interested” items (negative class), which however is an invalid assumption in practice.
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