Title :
Trust-based social item recommendation: A case study
Author :
Xing Xing ; Weishi Zhang ; Zhichun Jia ; Xiuguo Zhang
Author_Institution :
Sch. of Informational Sci. & Technol., Dalian Maritime Univ., Dalian, China
Abstract :
In this paper, we present a trust metric which leverages the user similarities, social relationships and trust propagations for measuring the trust between pairs of users in social networks. According to the trust metric, we propose a trust-based recommendation method for top-k item recommendation. A case study is conducted on Sina Weibo, which is one of the most popular Social Network Sites (SNS) in China. The experimental results demonstrate that our method outperforms the collaborative filtering based method.
Keywords :
collaborative filtering; recommender systems; security of data; social networking (online); China; Sina Weibo; collaborative filtering based method; social network sites; social relationship; top-k item recommendation; trust metric; trust propagation; trust-based social item recommendation; user similarity; collaborative filtering; recommender systems; social networks; trust-based recommendation;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4673-2963-7
DOI :
10.1109/ICCSNT.2012.6526106
