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Implementing a Rating-Based Item-to-Item Recommender System i...

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User personalization and profiling is key to many succesful Web sites. Consider that there is considerable free content on the Web, but comparatively few tools to help us organize or mine such content for specific purposes. One solution is to ask users to rate resources so that they can help each other find better content: we call this rating-based collaborative filtering. This paper presents a database-driven approach to item-to-item collaborative filtering which is both easy to implement and can support a full range of applications.

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