Recurrent Recommender NetworksEI

    Cited by: 241|Bibtex|40|

    WSDM, pp. 495-503, 2017.

    Abstract:

    Recommender systems traditionally assume that user profiles and movie attributes are static. Temporal dynamics are purely reactive, that is, they are inferred after they are observed, e.g. after a user's taste has changed or based on hand-engineered temporal bias corrections for movies. We propose Recurrent Recommender Networks (RRN) that...More
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