User Interests Modeling Based on Multi-source Personal Information Fusion and Semantic Reasoning
User interests are usually distributed in different systems on the Web. Traditional user interest modeling methods are not designed for integrating and analyzing interests from multiple sources, hence, they are not very effective for obtaining comparatively complete description of user interests in the distributed environment. In addition, previous studies concentrate on the text level analysis of user interests, while semantic relationships among interests are not fully investigated. This might cause incomplete and incorrect understanding of the discovered interests, especially when interests are from multiple sources. In this paper, we propose an approach of user interest modeling based on multi-source personal information fusion and semantic reasoning. We give different fusion strategies for interest data from multiple sources. Further more, we investigate the semantic relationship between users’ explicit interests and implicit interests by reasoning through concept granularity. Semantic relatedness among interests are also briefly illustrated for information fusion. Illustrative examples based on multiple sources on the Web (e.g. microblog system Twitter, social network sites Facebook and LinkedIn, personal homepage, etc.) show that proposed approach is potentially effective.
KeywordsSocial Network Site Domain Ontology Fusion Strategy User Interest Granular Computing
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