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Semantic Based Web Mining for Recommender Systems

机译:推荐系统基于语义的Web挖掘

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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.
机译:如今,有选择地进行个性化信息恢复的有效机制的可用性是Web用户的主要需求之一。在最近几年中,已经开发了一些具有智能机制的系统,这些机制可以进行个性化推荐。但是,这些推荐系统存在一些重要的缺点,无法完全满足其用户的需求。在这项工作中,提出了一种将关联规则挖掘方法与特定领域本体的定义相结合的方法,以便克服电影推荐系统中的这些问题。

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