Categorical-attributes-based item classification for recommender systems

    RecSys '18: Twelfth ACM Conference on Recommender Systems Vancouver British Columbia Canada October, 2018, pp. 320-328, 2018.

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    Abstract:

    Many techniques to utilize side information of users and/or items as inputs to recommenders to improve recommendation, especially on cold-start items/users, have been developed over the years. In this work, we test the approach of utilizing item side information, specifically categorical attributes, in the output of recommendation models ...More

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