期刊名称：International Journal of Business and Management
印刷版ISSN：1833-3850
电子版ISSN：1833-8119
出版年度：2009
卷号：4
期号：7
页码：10
DOI：10.5539/ijbm.v4n7P10
出版社：Canadian Center of Science and Education
摘要：The prosperity of e-commerce has changed the whole outlook of traditional trading behavior. More and more people are willing to conduct Internet shopping. However, the massive product information provided by the Internet Merchants causes the problem of information overload and this will reduces the customer’s satisfaction and interests. To overcome this problem, a recommender system based on web mining is proposed in this paper. The system utilizes web mining techniques to trace the customer’s shopping behavior and learn his/her up-to-date preferences adaptively. The experiments have been conducted to evaluate its recommender quality and the results show that the system can give sensible recommendations, and is able to help customers save enormous time for Internet shopping.
