An Optimization Method For Recommendation System Based On User Implicit Behavior

摘要：

　　Collaborative filtering is the most worldwide and personalized video recommendation technology. As collaborative filtering recommendation system is often faced with the problem of matrix sparse on user rating. Via the introduction of the concept of collaborative filtering and the analysis of user behaviors and solution to the problem of sparse existing recommendation systems, this paper puts forward with an optimization algorithm, combining with implicit user behavior and verify the effectiveness of the optimization algorithm through the experiment.

关键词： component: On-line Video Recommendation System Collaborative Filtering Algorithm User Behavior Analysis Sparsity

作者: Peng Yi Cheng Yang Chen Li Meng Chen

作者单位: Information Engineering School Communication University of China Beijing China

会议类型: 国际会议

会议名称: 2015 Fifth International Conference on Instrumentation and Measurement,Computer,Communication and Control (IMCCC2015)(第五届仪器测量、计算机通信与控制国际会议)

会议地点: 秦皇岛

会议语种:英文

页码: 1537-1540

在线出版日期: 2015-09-18（万方平台首次上网日期，不代表论文的发表时间）