Text retrieval and filtering: analytic models of performance
Text retrieval and filtering: analytic models of performance
Experience with personalization of Yahoo!
Communications of the ACM
Communications of the ACM
A personalized television listings service
Communications of the ACM
Intelligent profiling by example
Proceedings of the 6th international conference on Intelligent user interfaces
Modern Information Retrieval
A new structure for news editing
IBM Systems Journal
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Intelligent assistance for teachers in collaborative e-learning environments
Computers & Education
ITWP'03 Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization
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A systems approach to the automatic and adaptive personalization of Internet news is described. Implemented on the client side as a lightweight, transparent software system, this approach is based on implicit user feedback, thereby preserving privacy while avoiding the constant recustomization needed in explicit schemes. The system consists of two modules: (1) a profiling agent, which unobtrusively monitors news reading patterns to track interest in different topics while acting as a proxy server on the user's computer; (2) and an action agent, which uses the profile information to retrieve, filter, and present news articles. A prototype of the system was implemented and evaluated over a two week period. Precisions (the percentages of relevant articles returned by the system) ranging from 60-95% were observed for profiles representing various combinations of interests. The system also responded very well to simulated changes in user interests, returning rapidly increasing numbers of articles relevant to newly developed interests.