Experimental evaluation of context-dependent collaborative filtering using item splitting
User Model. User-Adapt. Interact., pp. 7-34, 2014.
Recommender SystemsCollaborative filteringContextItem splitting
Collaborative Filtering (CF) computes recommendations by leveraging a historical data set of users' ratings for items. CF assumes that the users' recorded ratings can help in predicting their future ratings. This has been validated extensively, but in some domains the user's ratings can be influenced by contextual conditions, such as the ...More
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