A Survey of Recommendation Systems in Electronic Commerce

Abstract

In an electronic commerce (E-commerce) environment, information users or online customers may experience information overload and make use of services that seek to help them in selecting from an overwhelming array of information or products. Merchandisers too may seek to better manage customer relationships that lead to higher customer satisfaction and loyalty. In response, recommendation systems have emerged as a class of e-service that not only addresses the challenge of information overload by suggesting information or products that are of most interest to users, but also facilitates the delivery of such services to customers. This chapter aims at providing a comprehensive review of recommendation approaches and their associated techniques. Broadly, recommendation systems can be classified into popularity-based, content-based, collaborative-filtering-based, association-based, demographics-based, and reputation-based recommendation approaches. Representative recommendation systems will be depicted in this chapter.