A Collaborative Filtering Algorithm Based on Double Clustering and User Trust

被引：0
|
作者：
Tang, Tonglong [1 ]
Li, Xiaoyu [1 ]
机构：
[1] Zhengzhou Unvers, Sch Informat Engn, Zhengzhou 450001, Peoples R China
来源：
PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON SENSOR NETWORK AND COMPUTER ENGINEERING | 2016年 / 68卷
关键词：
Collaborative filtering algorithm; Double clustering; User trust; Score prediction; Recommender system;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
A collaborative filtering algorithm based on double clustering and user trust to solve data sparse and cold start problem is present. This algorithm uses user-clustering matrix to measure the user's degree of similarity, which could reduce the dimension of the user-item matrix. On the other hand it uses user level trust to perform predictions in rating predicting step. The experiments results show that this method could relieve the sparsity problem and improve the accuracy of the prediction results.
引用
收藏
页码：31 / 37
页数：7
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