A collaborative filtering recommendation algorithm based on user interest change and trust evaluation

被引：11

作者：

Chen Z. ^{[1
]}

Jiang Y. ^{[1
]}

Zhao Y. ^{[1
]}

机构：

[1] Institute of Information Engineering, Yangzhou University, Yangzhou

来源：

International Journal of Digital Content Technology and its Applications | 2010年 / 4卷 / 09期

关键词：

Collaborative filtering; Similarity measure; Time weight; Trust evaluation;

D O I：

10.4156/jdcta.vol4.issue9.13

中图分类号：

学科分类号：

摘要：

Collaborative filtering algorithm is one of the most successful technologies used in personalized recommendation system. However, traditional algorithms focus only on user ratings and do not consider the changes of user interest and the credibility of ratings data, which affected the quality of the system's recommendation seriously. To solve this problem, this paper presents an improved algorithm. Firstly, the user's rating is given a weight by a gradual time decrease and credit assessment in the course of user similarity measurement, and then several users highly similar with active user are selected as his neighbor. Finally, the active user's preference for an item can be represented by the average scores of his neighbor. Experimental results show that the algorithm can make the neighbor recognition more accurately and enhance the quality of recommendation system effectively.

引用

页码：106 / 113

页数：7

共 11 条

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