Automatic personalization based on Web usage mining
Communications of the ACM
Hybrid personalized recommender system using centering-bunching based clustering algorithm
Expert Systems with Applications: An International Journal
Interest-based user grouping model for collaborative filtering in digital libraries
ICADL'04 Proceedings of the 7th international Conference on Digital Libraries: international collaboration and cross-fertilization
A collaborative filtering based re-ranking strategy for search in digital libraries
ICADL'05 Proceedings of the 8th international conference on Asian Digital Libraries: implementing strategies and sharing experiences
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In this paper, we describe a prototype system, called PASS (Personalized Active Service System), which provides personalized services for digital libraries. User profiles are represented as probabilistic distributions of interests over different domains. The system realizes content-based filtering by computing the similarity of probabilistic distributions between documents and user profiles. In addition the system realizes collaborative filtering by clustering similar user profiles. Experimental results show its performance satisfactory.