Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Mei, Jian-Pinga; * | Yu, Hanb | Shen, Zhiqib; c | Miao, Chunyanb; c
Affiliations: [a] College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, Zhejiang, China | [b] Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly, NTU, Singapore | [c] School of Computer Engineering, Nanyang Technological University, Singapore
Correspondence: [*] Corresponding author: Jian-Ping Mei, College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, Zhejiang, China. Tel.: +86 571 8529 0527; E-mail:[email protected]
Abstract: Trustworthy computing has recently attracted significant interest from researchers in several fields including multi-agent systems, social network analysis, and recommender systems. As an additional dimension of information to past rating history, trust has been shown to be helpful for improving the accuracy of recommendations. Studies on the relationship between trust and rating behaviors may provide insights into the formation of trust in the context of online community, and lead to possible indicators for the effective use of trust in recommendations. In this paper, we study people's trust and rating behavior with the Epinions dataset. Epinions.com is a popular product review website allowing users to rate various categories of products, and establish a list of trustworthy users. We perform correlation analysis of activeness and trustworthiness defined by the number of ratings and the number of trustors to derive findings that can help the design of new decision support mechanisms in trust-based recommender systems. We then propose a trustee-influence based trust model where a trustee's activeness or trustworthiness is used to determine trust relationships. This trust model is incorporated into a memory-based and matrix factorization recommender systems to support online purchasing decision-making. Experimental results demonstrate the effectiveness of the proposed trust model for recommendation.
Keywords: Recommender system, trust, number of ratings, Epinions, social influence
DOI: 10.3233/IDA-150479
Journal: Intelligent Data Analysis, vol. 21, no. 2, pp. 263-277, 2017
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]