Selecting content-based features for collaborative filtering recommenders
RecSys, pp. 407-410, 2013.
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
Get fulltext within 24h
Full Text (Upload PDF)
PPT (Upload PPT)