Claypool, Mark L.
Many online newspapers provide news without consideration for reader's tastes. Collaborative filtering solves this problem by recommending articles based upon ratings by others. Collaborative filtering can be enhanced by content-based filtering when ratings are sparse. We applied a blend of collaborative and content-based filtering to an online newspaper, the Worcester Telegram and Gazette. Our system consists of a web-based interface, a back-end recommendation engine, and a database. We analyze results of the project and propose direction for future work.
Worcester Polytechnic Institute
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