基于用户等级的协同过滤推荐算法  

A User Grade-based Collaborative Filtering Recommendation Algorithm

作　　者：高滢[1] 齐红[1] 刘亚波[1] 刘大有[1] 

机构地区：[1]吉林大学计算机科学与技术学院,长春130012

出　　处：《吉林大学学报（理学版）》2008年第3期489-493,共5页Journal of Jilin University:Science Edition

基　　金：国家自然科学基金重大项目基金(批准号:60496321);国家自然科学基金(批准号:60573073;60773099);国家863高技术研究发展计划项目基金(批准号:2006AA10Z245;2006AA10A309);吉林省科技发展计划重大项目基金(批准号:20020303);吉林省科技发展计划项目基金(批准号:20030523);欧盟项目(批准号:TH/AsiaLink/010(111084))

摘　　要：提出一种基于用户等级的协同过滤推荐算法,解决了传统协同过滤推荐算法的扩展性问题.该算法首先定义用户等级函数,依据用户所评价的项目数确定用户等级;并通过仅在用户等级的邻域内查找近邻的方法,提高协同过滤推荐的效率.实验结果表明,该算法与传统协同过滤推荐算法相比,在不影响推荐质量的前提下,极大地提高了推荐效率.A user grade-based collaborative filtering recommendation algorithm is presented in this paper. It solves the scalability problem of traditional collaborative filtering algorithm. It defines a user grade function firstly, which determines users＇ grade according to the number of their rating items, and by means of finding neighbors for a target user, it only considers the candidates in his near grade, so the efficiency increases. Both theory and experimental results show that this algorithm improves recommendation efficiency greatly compared with traditional collaborative filtering, and at the same time the recommendation quality does not decrease.

关 键 词：协同过滤 用户等级 推荐算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]