Improving Personalized Services in Mobile Commerce by a Novel Multicriteria Rating Approach
With the rapid growth of wireless technologies and mobile devices, there is a great demand for personalized services in mcommerce. Collaborative filtering (CF) is one of successful techniques to produce personalized recommendations for users. This paper proposes a novel approach to improve CF algorithms, where the contextual information of a user and the multicriteria ratings of an item are considered besides the typical information on users and items. The multilinear singular value decomposition (MSVD) technique is utilized to explore both explicit relations and implicit relations among user, item and criterion. We implement the approach in an existing m-commerce platform, and encouraging experimental results demonstrate its effectiveness.
Personalized service collaborative filtering m-commerce
Qiudan Li Chunheng Wang Guanggang Geng
Key Laboratory of Complex Systems and Intelligence Science,Institute of Automation, Chinese Academy of Sciences, Beijing
国际会议
第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)
北京
英文
2008-04-21（万方平台首次上网日期，不代表论文的发表时间）