Rough Set Based Personalized Recommendation in Mobile Commerce

Authors:
Lei Shi;Li Zhang;Xinming Ma;Xiaohong Hu
Affiliations:
College of Information and Management Science, Henan Agricultural University, Zhengzhou, China 450002;College of Information and Management Science, Henan Agricultural University, Zhengzhou, China 450002;College of Information and Management Science, Henan Agricultural University, Zhengzhou, China 450002;College of Information and Management Science, Henan Agricultural University, Zhengzhou, China 450002
Venue:
AMT '09 Proceedings of the 5th International Conference on Active Media Technology
Year:
2009

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Abstract

Mobile commerce (M-commerce) combines the advantages of electronic commerce with the mobility and freedom of wireless devices such as cellular telephones and PDAs. As M-Commerce become more and more prevalent to people, it is very critical to provide the right information to the right customers. In this paper, a novel personalized recommendation method based on tolerance rough set is proposed to help customers purchase needed products conveniently. Tolerance rough set is used to deal with latent information and capture customer preference according to both the customer's interests and his current context.