Semantic Based Web Mining for Recommender Systems

Availability of efficient mechanisms for selective and personalized recovery of information is nowadays one of the main demands of Web users. In the last years some systems endowed with intelligent mechanisms for making personalized recommendations have been developed. However, these recommender systems present some important drawbacks that prevent from satisfying entirely their users. In this work, a methodology that combines an association rule mining method with the definition of a domain-specific ontology is proposed in order to overcome these problems in the context of a movies’ recommender system.

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