Improving User Topic Interest Profiles by Behavior Factorization
WWW, pp. 1406-1416, 2015.
Many recommenders aim to provide relevant recommendations to users by building personal topic interest profiles and then using these profiles to find interesting contents for the user. In social media, recommender systems build user profiles by directly combining users' topic interest signals from a wide variety of consumption and publish...More
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