An Improved Collaborative Filtering Recommendation Algorithm

摘要：

The core of the classic collaborative filtering algorithms about similar calculation are designed on the basis of the user-item matrix model. This paper proposes an improved collaborative filtering algorithm on the basis of the user-item cube model, which takes care of the factor of the data produced when the user purchased the item. The algorithm attaches the corresponding weight to the date factor, and then the corresponding weight is used to the calculation of the similarity. This method increases the accuracy of the recommendation system significantly.

关键词： Web Mining E-Commerce Personalized Recommendation Collaborative Filtering

作者: LIU Jian-ping WANG Yong YAN Feng-hua

作者单位: The College of Informatics & Electronics Zhejiang Sci-Tech University Hangzhou,China

会议类型: 国际会议

会议名称: The First International Conference on Networking and Distributed Computing(第一届网络与分布式计算国际会议 ICNDC 2010)

会议地点: 杭州

会议语种:英文

页码: 194-198

在线出版日期: 2010-10-21（万方平台首次上网日期，不代表论文的发表时间）