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Title: User preference modeling by trust propagation for rating prediction
Authors: Lei, Y
Chen, C
Chen, Q
Li, W 
Keywords: Trust propagation
Rating prediction
User preference modeling
Issue Date: 2015
Publisher: Institute of Electrical and Electronics Engineers
Source: 2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity), Chengdu,19-21 Dec 2015, p. 500-506 How to cite?
Abstract: To alleviate the issue of data sparsity in collaborative filtering (CF), a number of trust-aware recommendation methods have been proposed recently. However, the existing methods that straightforwardly utilize trust relations to model user similarities in ratings or preference features can hardly provide the in-depth understanding of the trust and its relationship to user preference. They also fail to systematically model the mutual influence among users via the truster-user-trustee propagation. In this paper, we propose a novel integrated matrix factorization framework to model user preference, trust relation and the relationship between them in a systematic way. The proposed framework is able to describe how and how much users' preferences change and influence each other with trust propagation over the network. As a result, more effective user preference features can be learned from both rating and trust data. Experimental results on three real-world datasets show that our proposed methods outperform the state-of-theart CF and trust-aware methods.
ISBN: 978-1-5090-1893-2 (electronic)
978-1-5090-1892-5 (CD-ROM)
DOI: 10.1109/SmartCity.2015.119
Appears in Collections:Conference Paper

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