计算机工程2012，Vol.38Issue(24)：50-52,3.
基于模糊聚类的协同过滤算法
Collaborative Filtering Algorithm Based on Fuzzy Clustering
摘要
Abstract
To deal with the sparsity and expansibility of traditional collaborative filtering algorithm, which affects the accuracy of their recommendations, a collaborative filtering algorithm based on fuzzy cluster is proposed in this paper. It applies fuzzy clustering method to cluster the item, and computes the similarity between the users by analyzing the average ratings that the k users rate the items of the clusters. It predicts the ratings of the items that the k users rate based on the ratings of the neighbors that they rate, chooses the first n recommendations. Experimental result demonstrates that the algorithm can improve the accuracy of recommendation under the condition of the extreme sparsity of user rating data.关键词
电子商务/推荐系统/模糊聚类/协同过滤/推荐精度Key words
e-commerce/ recommendation system/ fuzzy clustering/ collaborative filtering/ recommendation accuracy分类
信息技术与安全科学引用本文复制引用
王明佳,韩景倜,韩松乔..基于模糊聚类的协同过滤算法[J].计算机工程,2012,38(24):50-52,3.基金项目
国家自然科学基金资助项目(61003022,71271126) （61003022,71271126）
上海高校青年教师培养资助计划基金资助项目 （）
