Personalized Recommendation Algorithm based on SVM

摘要：

with the development of the E-commerce,personalized product and service have become a developing trend gradually. To meet the personalized needs of customers in E-commerce, a new personalized recommendation algorithm based on support vector machine was proposed in the paper. First, user profile was organized hierarchically into field information and atomic information needs, considering similar information needs in the group users. Support vector machine was adopted for collaborative recommendation in classification mode, and then Vector Space Model was used for content-based recommendation according to atomic information needs. The algorithm had overcome the demerit of using collaborative or content-based recommendation solely, which improved the precision and recall in a large degree. It also fits for large scale group recommendation. The algorithm could also used in personalized recommendation service system based on E-commerce.

作者: Bing Wu Luo Qi XiongFeng

作者单位: School of Management, Wuhan University of Technology Wuhan 430070, China School of Electrical Engineering, Wuhan Institute of technology, Wuhan 430070, China；Department of I

会议类型: 国际会议

会议名称: 2007年通信、电路与系统国际会议(2007 International Conference on Communications,Circuits and Systems Proceedings)

会议地点: 日本福冈

会议语种:英文

在线出版日期: 2007-07-11（万方平台首次上网日期，不代表论文的发表时间）