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Erschienen in:
2012 | OriginalPaper | Buchkapitel
A Reinforcement Learning Based Tag Recommendation
verfasst von : Feng Ge, Yi He, Jin Liu, Xiaoming Lv, Wensheng Zhang, Yiqun Li
Erschienen in: Practical Applications of Intelligent Systems
Verlag: Springer Berlin Heidelberg
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This paper proposes a reinforcement learning based tag recommendation algorithm to deal with the data sparseness that affects the performance stability of collaborative filtering algorithms. Our algorithm integrates user tags into traditional collaborative filtering algorithms and attaching importance to user interest shift in the process of user interest learning process. Empirical Cases of comparing with traditional collaborative filtering algorithms indicate that our recommend algorithm exhibits better performance competition.