Movie Recommendation Framework Using Associative Classification and a Domain Ontology

摘要: The increasing acceptance of web recommender systems is mainly due to improvements achieved through intensive research carried out over several years. Numerous methods have been proposed provide users with more and reliable recommendations, from the traditional collaborative filtering approaches sophisticated mining techniques. In this work, we propose a complete framework deal some important drawbacks still present in current systems. Although addressed movies’ recommendation, it can be easily extended other domains. It manages different predictive models for making recommendations depending on specific situations. These are induced by data algorithms using as input both product user attributes structured according particular domain ontology.