Discovering User Interests from Web Browsing Behavior: An Application to Internet News Services
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 7 - Volume 7
Learning implicit user interest hierarchy for context in personalization
Applied Intelligence
Towards a Tag-Based User Model: How Can User Model Benefit from Tags?
UM '07 Proceedings of the 11th international conference on User Modeling
Granular computing applied to ontologies
International Journal of Approximate Reasoning
User interests: definition, vocabulary, and utilization in unifying search and reasoning
AMT'10 Proceedings of the 6th international conference on Active media technology
User-centric query refinement and processing using granularity-based strategies
Knowledge and Information Systems
Research interests: their dynamics, structures and applications in unifying search and reasoning
Journal of Intelligent Information Systems
Interest logic and its application on the web
KSEM'11 Proceedings of the 5th international conference on Knowledge Science, Engineering and Management
User interests driven web personalization based on multiple social networks
Proceedings of the 4th International Workshop on Web Intelligence & Communities
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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.