Collaborative filtering recommendation algorithm based on weighed grade

被引：0

作者：

Wang, Huaibin ^{[1
,2
]}

Guo, Jingze ^{[1
,2
]}

Wang, Chundong ^{[1
,2
]}

机构：

[1] Key Laboratory of Computer Vision and System, Tianjin University of Technology, Ministry of Education, Tianjin

[2] Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Ministry of Education, Tianjin

来源：

Journal of Computational Information Systems | 2014年 / 10卷 / 23期

关键词：

Accuracy; Collaborative filtering; Recommendation; Weighed;

D O I：

10.12733/jcis12380

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In traditional collaborative filtering recommendation algorithms, users' grades are used to calculate the similarity between different items, which is used to predict the result of recommendation further. Same grades for different items from same user can't demonstrate the similarity between the items and will decrease the influence on items not so popular. To improve reliability of similarity of calculating, this paper weighs the grades according to proportion of corresponding grades based on the traditional algorithms, which is called collaborative filtering recommendation algorithm based on weighed grades. The result of experiments demonstrates this method of calculating considering the influence on items not so popular that traditional methods don't [1], increasing the accuracy of recommendation. Copyright © 2014 Binary Information Press.

引用

页码：9995 / 10001

页数：6

共 14 条

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