A Collaborative Filtering Recommendation Algorithm with Time Adjusting Based on Attribute Center of Gravity Model

摘要：

　　In the collaborative filtering recommendation technology, the similarity measurement part plays a vital role,and similarity measurement accuracy seriously affects the similarity measurement part and all the subsequent parts.However, there are many shortcomings in the similarity measurement part of traditional memory-based collaborative filtering recommendation technology, in order to solve the inaccuracy under special circumstances, this paper proposes an improved algorithm, a collaborative filtering recommendation algorithm with time adjusting based on attribute center of gravity model, through altering the process of similarity calculation.Simulation results show that the improved algorithm gains a higher recommendation accuracy, compared with the traditional algorithms.

关键词： collaborative filtering similarity measurement inaccuracy center of gravity time-dimensional adjustment

作者: Liangyou Gao Mengxing Huang

作者单位: College of Information Science &Technology Hainan University Haikou 570228, China

会议类型: 国际会议

会议名称: The 12th Web Information System and Application Conference第十二届全国Web信息系统及其应用学术会议(WISA2015)、全国第十次语义Web 与本体论学术研讨会(SWON2015)、全国第九次电子政务技术及应用学术研讨会(EGTA2015)

会议地点: 济南

会议语种:英文

页码: 197-200

在线出版日期: 2015-09-11（万方平台首次上网日期，不代表论文的发表时间）