AAAI Publications, Workshops at the Twenty-Seventh AAAI Conference on Artificial Intelligence

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Supervised Topic Model with Consideration of User and Item
Sheng Wang, Fangtao Li, Ming Zhang

Last modified: 2013-06-29


In this paper, we propose a new supervised topic model by incorporating the user and the item information. The proposed model can simultaneously utilize the textual topic and user-item factors for label prediction. We conduct prediction experiment with a public review dataset. The results demonstrate the advantages of our model. It shows clear improvement compared with traditional supervised topic model and recommendation method.


topic model;recommender system;matrix factorization

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