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- W2017922319 abstract "Recommender systems predict user preferences based on a range of available information. For systems in which users generate streams of content (e.g., blogs, periodically-updated newsfeeds), users may rate the produced content that they read, and be given accurate predictions about future content they are most likely to prefer. We design a distributed mechanism for predicting user ratings that avoids the disclosure of information to a centralized authority or an untrusted third party: users disclose the rating they give to certain content only to the user that produced this content." @default.
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- W2017922319 date "2011-10-23" @default.
- W2017922319 modified "2023-09-26" @default.
- W2017922319 title "Distributed rating prediction in user generated content streams" @default.
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- W2017922319 doi "https://doi.org/10.1145/2043932.2043948" @default.
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