Rough set based personalized recommendation in mobile commerce

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. © 2009 Springer-Verlag.