Bayesian Wishart matrix factorization

    Data Min. Knowl. Discov., Volume 30, Issue 5, 2016, Pages 1166-1191.

    Cited by: 3|Bibtex|Views12|Links
    EI
    Keywords:
    Recommender systemsTemporal dynamicsMatrix factorization

    Abstract:

    User tastes are constantly drifting over time as users are exposed to different types of products. The ability to model the tendency of both user preferences and product attractiveness is vital to the success of recommender systems (RSs). We propose a Bayesian Wishart matrix factorization method to model the temporal dynamics of variation...More

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