基于项目与客户聚类的协同过滤推荐方法  

Collaborative filtering recommendation algorithm based on clustering of items and customers

作　　者：张娜[1] 何建民[1] 

机构地区：[1]合肥工业大学管理学院,安徽合肥230009

出　　处：《合肥工业大学学报（自然科学版）》2007年第9期1159-1162,共4页Journal of Hefei University of Technology：Natural Science

基　　金：国家自然科学基金资助项目(7067097)

摘　　要：文章给出了一种基于项目与客户聚类的协同过滤推荐方法,将聚类分析与协同过滤方法紧密结合;通过降低项目空间维数,减少了用户在寻找最近邻邻居的搜索强度,增强了推荐算法的实时性,提高了推荐服务的质量。A collaborative filtering recommendation algorithm based on clustering of items and customers is proposed ,which combines clustering analysis with the collaborative filtering method. The given algorithm reduces the search space for nearest neighbor search through lowering the dimension of the item space, thus improving the real-time performance of the recommendation algorithm and the quality of the recommendation service.

关 键 词：协同过滤 聚类分析 电子商务系统 个性化推荐 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]