Item-based Collaborative Filtering Algorithm Based on Group Weighted Rating
Item-based collaborative filtering algorithm is one of the main collaborative filtering algorithms. However, its recommendation quality is seriously influenced by the sparsity of user ratings. To solve the problem, an improved item-based collaborative filtering algorithm based on group weighted rating is proposed. The union of user rating items is used as the basis of similarity computing between items, moreover a group weighted rating method has been proposed to compute and complete the missing values in the union of user rating items for decreasing the sparsity. The experimental results show that the new algorithm can efficiently improve recommendation quality.
E-commerce Recommender systems Group weighted rating Collaborative filtering
Song Zhang Li Ma
School of Computer ScienceSichuan Normal UniversityChengdu, China Department of Computer Science Sichuan Post and Telecommunication College Chengdu, China
国际会议
哈尔滨
英文
513-517
2011-01-18（万方平台首次上网日期，不代表论文的发表时间）