Communications of the ACM
Learning to recommend from positive evidence
Proceedings of the 5th international conference on Intelligent user interfaces
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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In this paper, an approach to learning user interests is presented. It relies on positive evidences only, in consideration of the fact that users rarely supply the ratings needed by traditional learning algorithms, specifically not negative examples. Learning results are explicitly represented to account for the fact that in the area of user modeling explicit representations are known to be considerably more useful than purely implicit representations. A content-based recommendation approach is presented. The described framework has been extensively tested in an information system.