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• 计算机科学 • 上一篇    下一篇

基于用户等级的协同过滤推荐算法

高 滢, 齐 红, 刘亚波, 刘大有   

  1. 吉林大学 计算机科学与技术学院, 长春 130012
  • 收稿日期:2007-05-28 修回日期:1900-01-01 出版日期:2008-05-26 发布日期:2008-05-26
  • 通讯作者: 刘大有

A User Gradebased Collaborative Filtering Recommendation Algorithm

GAO Ying, QI Hong, LIU Yabo, LIU Dayou   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2007-05-28 Revised:1900-01-01 Online:2008-05-26 Published:2008-05-26
  • Contact: LIU Dayou

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.

关键词: 协同过滤, 用户等级, 推荐算法

Abstract: 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.

Key words: collaborative filtering, user grade, recommendation algorithm

中图分类号: 

  • TP391