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- W2009657880 abstract "In recent years, many systems and approaches for recommending information, products or other objects have been developed. In these systems, often machine learning methods that need training input to acquire a user interest profile are used. Such methods typically need positive and negative evidence of the user's interests. To obtain both kinds of evidence, many systems make users rate relevant objects explicitly. Others merely observe the user's behavior, which fairly obviously yields positive evidence; in order to be able to apply the standard learning methods, these systems mostly use heuristics that attempt to find also negative evidence in observed behavior." @default.
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- W2009657880 date "2000-01-09" @default.
- W2009657880 modified "2023-10-12" @default.
- W2009657880 title "Learning to recommend from positive evidence" @default.
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- W2009657880 doi "https://doi.org/10.1145/325737.325858" @default.
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