Information filtering is a key technology for the creation of Web sites, which are adapted to the user's needs. In this paper we identify collaborative filtering and content-based filtering as independent technologies for information filtering. We apply both technologies in our prototype user-adapting Web site, the Active WebMuseum, a recommender system for art paintings. Our new approach extends existing user profiles with content-based information gained through automatic image indexing. These extensions lead to a better performing collaborative filtering system. We validate our approach in on-line experiments.
Using color and texture indexing to improve collaborative filtering of art paintings
CBMI 1999, 1st European Workshop on Content-Based Multimedia Indexing, October 25-27 1999, Toulouse, France
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