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- W2954028181 abstract "In Web services dealing with user-generated content (UGC), a user can have two roles: a role of a consumer and that of a producer. Since most item recommendation models have only considered the role of a user as a consumer, how to leverage the two roles to improve UGC recommendation accuracy has been underexplored. In this paper, based on the state-of-the-art UGC recommendation method called CPRec (consumer and producer based recommendation), we propose ABCPRec (adaptively bridging CPRec). Unlike CPRec, which assumes that the two roles of a user are always related to each other, ABCPRec adaptively bridges the two roles according to the similarity between her nature as a consumer and that as a producer. This enables the model to learn each user's characteristics as both a consumer and a producer and to recommend items to each user more accurately. By using two real-world datasets, we showed that our proposed method significantly outperformed comparative methods in terms of AUC." @default.
- W2954028181 created "2019-07-12" @default.
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- W2954028181 date "2019-07-18" @default.
- W2954028181 modified "2023-09-23" @default.
- W2954028181 title "ABCPRec" @default.
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- W2954028181 doi "https://doi.org/10.1145/3331184.3331335" @default.
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