A Collaborative Tagging System for Personalized Recommendation in B2C Electronic Commerce
In recent years, the B2C e-commerce achieved a rapid development on a global scope; more and more people began to use the Internet for shopping. However, the exponentially increasing information provided by Internet enterprises causes the problem of overloaded information, and this inevitably reduces the customers satisfaction and loyalty. One way to overcome such problem is to build personalized recommender systems to retrieve product information that really interests the customers. The rapid development of Web 2.0 provides new ideas for personalized recommendation. In this paper we introduce the collaborative filtering, knowledge-based approaches and hybrid approaches in building recommender systems and discuss the strengths and weaknesses of each approach. we propose collaborative tagging system to provide personalized product information to customers in B2C e-commerce websites and describe the systems architecture and point the systems advantage.
Recommender System Collaborative Tagging Syste Concept Space
Yuying Jiao Gaohui Cao
Center for Studies of Information Resources Wuhan University Wuhan, China
国际会议
上海
英文
2007-09-21（万方平台首次上网日期，不代表论文的发表时间）