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2017 | OriginalPaper | Chapter

Trust-Aware Recommendation in Social Networks

Authors : Yingyuan Xiao, Zhongjing Bu, Ching-Hsien Hsu, Wenxin Zhu, Yan Shen

Published in: Knowledge Science, Engineering and Management

Publisher: Springer International Publishing

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Abstract

With the popularity of online social networks, social network information is becoming increasingly important to improve recommendation effectiveness of the existing recommender systems. In this paper, we propose an improved trust-aware recommendation approach, called TRA. TRA constructs a new social trust matrix based on users’ trust relationships derived from online social networks to alleviate the problem of data sparsity, and meanwhile naturally fuses users’ preferences and their trusted friends’ favors together by means of probability matrix factorization. The experimental results show that TRA performs much better than the state-of-the art recommendation approaches.

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previous chapter Exploring Latent Bundles from Social Behaviors for Personalized Ranking
next chapter Connecting Factorization and Distance Metric Learning for Social Recommendations
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Metadata
Title
Trust-Aware Recommendation in Social Networks
Authors
Yingyuan Xiao
Zhongjing Bu
Ching-Hsien Hsu
Wenxin Zhu
Yan Shen
Copyright Year
2017
Book
Knowledge Science, Engineering and Management

Print ISBN: 978-3-319-63557-6

Electronic ISBN: 978-3-319-63558-3

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-63558-3_32

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