Abstract
Since the current Web is largely unorganized and there is a rapid growth of information volumes, the recommendation system whose major purpose is to reduce irrelevant content and to provide users with more pertinent and tailored information becomes an important research area. A key issue in this area is how to discover user's interest and behavior effectively. In this paper we investigate an approach to recommendation system based on user ontology and spreading activation model. Through combining the user ontology and spreading activation model, the capability of discovering of user's potential interests is enhanced. A prototype system is also dev.eloped base on this methodology.
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