JCC  Vol.2 No.14 , December 2014
Research of Collaborative Filtering Recommendation Algorithm for Short Text
Author(s) Chunxu Chao1, Shouning Qu2*, Tao Du1
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 often leads to a big difference between the result of recommendation and user’s real demands. In this paper, according to the traditional collaborative filtering algorithm, a new personalized recommendation algorithm is proposed. It traced user’s interest by using Ebbinghaus Forgetting Curve. Some experiments have been done. The results demonstrated that the new algorithm could indeed make a contribution to getting rid of user’s overdue interests and discovering their real-time interests for more accurate recommendation.

Cite this paper
Chao, C. , Qu, S. and Du, T. (2014) Research of Collaborative Filtering Recommendation Algorithm for Short Text. Journal of Computer and Communications, 2, 59-66. doi: 10.4236/jcc.2014.214006.
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