Selecting content-based features for collaborative filtering recommenders

RecSys, pp. 407-410, 2013.

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Abstract:

We study the problem of scoring and selecting content-based features for a collaborative filtering (CF) recommender system. Content-based features play a central role in mitigating the ``cold start'' problem in commercial recommenders. They are also useful in other related tasks, such as recommendation explanation and visualization. Howev...More

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