Research on social recommender systems

被引：0

作者：

Meng, Xiang-Wu ^{[1
,2
]}

Liu, Shu-Dong ^{[1
,2
]}

Zhang, Yu-Jie ^{[1
,2
]}

Hu, Xun ^{[1
,2
]}

机构：

[1] Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunication, Beijing,100876, China

[2] School of the Computer Science, Beijing University of Posts and Telecommunication, Beijing,100876, China

来源：

Ruan Jian Xue Bao/Journal of Software | 2015年 / 26卷 / 06期

关键词：

Collaborative filtering - Inference engines - Factorization;

D O I：

10.13328/j.cnki.jos.004831

中图分类号：

学科分类号：

摘要：

Social recommender systems have recently become one of the hottest topics in the domain of recommender systems. The main task of social recommender system is to alleviate data sparsity and cold-start problems, and improve its performance utilizing users' social attributes. This paper presents an overview of the field of social recommender systems, including trust inference algorithms, key techniques and typical applications. The prospects for future development and suggestions for possible extensions are also discussed. ©2015 ISCAS.

引用

页码：1356 / 1372

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