Read full paper at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=52497#.VJog-cCAM4 Author(s) Chunxu Chao 1 , Shouning Qu 2* , Tao Du 1 Affiliation(s) 1 School of Information Science and Engineering, University of Jinan, Jinan, China . 2 The Center of Information Network, University of Jinan, Jinan, China . ABSTRACT Short text, based on the platform of web2.0, gained rapid development in a relatively short time. Recommendation systems analyzing user’s interest by short texts becomes more and more important. Collaborative filtering is one of the most promising recommendation technologies. However, the existing collaborative filtering methods don’t consider the drifting of user’s interest. This ...
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