Personalized Recommender Systems Integrating Social Tags and Item Taxonomy

The social tags in web 2.0 are becoming another important information source to profile users' interests and preferences to make personalized recommendations. To solve the problem of low information sharing caused by the free-style vocabulary of tags and the long tails of the distribution of ta...

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Bibliographic Details
Published in:Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01 Vol. 1; pp. 540 - 547
Main Authors: Liang, Huizhi, Xu, Yue, Li, Yuefeng, Nayak, Richi, Weng, Li-Tung
Format: Conference Proceeding
Language:English
Published: Washington, DC, USA IEEE Computer Society 15.09.2009
IEEE
Series:ACM Conferences
Subjects:
Australia
Conferences
Information systems > Information retrieval > Document representation
Information systems > Information retrieval > Evaluation of retrieval results
Information systems > Information retrieval > Retrieval tasks and goals > Document filtering
Information systems > Information retrieval > Retrieval tasks and goals > Information extraction
Information systems > Information retrieval > Users and interactive retrieval > Personalization
Information systems > World Wide Web > Web searching and information discovery > Personalization
Information technology
Intelligent agent
Ontologies
personalization
Probability distribution
Recommender systems
social tags
Tagging
Taxonomy
Theory of computation > Semantics and reasoning > Program reasoning > Abstraction
Vocabulary
web 2.0
personalization
recommender systems
social tags
web 2.0
ISBN:0769538010, 9780769538013
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Summary:The social tags in web 2.0 are becoming another important information source to profile users' interests and preferences to make personalized recommendations. To solve the problem of low information sharing caused by the free-style vocabulary of tags and the long tails of the distribution of tags and items, this paper proposes an approach to integrate the social tags given by users and the item taxonomy with standard vocabulary and hierarchical structure provided by experts to make personalized recommendations. The experimental results show that the proposed approach can effectively improve the information sharing and recommendation accuracy.
ISBN:0769538010
9780769538013
DOI:10.1109/WI-IAT.2009.89