Research on personalized recommendation based on web usage mining using collaborative filtering technique

Authors:
Taowei Wang;Yibo Ren
Affiliations:
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:
WSEAS Transactions on Information Science 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. This paper presents a system architecture of personalized recommendation using collaborative filtering based on web usage mining and describes detailedly data preparation process. To improve recommending quantity, a new personalized recommendaton model is proposed in which takes the good consideration of URL related analysis and combines the K-means algorithm. Experimental results show that our proposed model is effective and can enhance the performance of recommendation.