Study on personalized recommendation based on collaborative filtering

Authors:
Taowei Wang;Aimin Yang;Yibo Ren
Affiliations:
Computer Science and Information Technology College, Zhejiang Wanli University, Ningbo, P. R. China;Computer Science and Information Technology College, Zhejiang Wanli University, Ningbo, P. R. China;Department of Computer, Zhejiang Business Technology Institute, Ningbo, P. R. China
Venue:
CEA'09 Proceedings of the 3rd WSEAS international conference on Computer engineering and applications
Year:
2009

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Abstract

Collaborative filtering is the most successful technology for building personalized recommendation system and is extensively used in many fields. In the paper, a system architecture of personalized recommendation using collaborative filtering based on web log is proposed and data preparation process is detailedly described. The paper also gives an improved k-means algorithm for clustering user transactions. Experimental results show that our proposed algorithm could increase recommendation precision.