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Learning and Revising User Profiles: The Identification of Interesting Web Sites

, and . Machine Learning, 27 (3): 313--331 (1997)

Abstract

. We discuss algorithms for learning and revising user profiles that can determine which World Wide Web sites on a given topic would be interesting to a user. We describe the use of a naive Bayesian classifier for this task, and demonstrate that it can incrementally learn profiles from user feedback on the interestingness of Web sites. Furthermore, the Bayesian classifier may easily be extended to revise user provided profiles. In an experimental evaluation we compare the Bayesian classifier to ...

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