DocumentCode
604451
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
fYear
2012
fDate
29-31 Dec. 2012
Firstpage
1050
Lastpage
1053
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location
Changchun
Print_ISBN
978-1-4673-2963-7
Type
conf
DOI
10.1109/ICCSNT.2012.6526106
Filename
6526106
Link To Document