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Trust Prediction Based on Interactive Relations Strength

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Applications and Techniques in Information Security (ATIS 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 557))

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Abstract

In online social network, trust is the basis of reliable interaction among users, and interaction relations also affect trust establishment. Although many researchers have studied approaches of trust model and prediction, most trust prediction methods are based on the existing trust network, and lack the in-depth study of user interaction and contents; therefore, it is not conducive to implement those trust prediction models, at the same time it also limits the scope of their applications. To deal with these issues, this paper presents a novel trust prediction framework based on both a trust network and the interactive contexts between users, and a kind of measurement mechanism is put forward to evaluate the strength of interaction relations. Combined with the existing trust network, a trust prediction threshold value is learned and used to predict unknown trust relations. Empirical experiments conducted on Epinions dataset show that the unknown trust relations can be effectively predicted combining with the user’s interaction behaviors, and the proposed method can improve the performance of the trust prediction model.

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Acknowledgments

This work is supported by the Software Innovative Team of Guilin University of Electronic Technology and Graduate Innovation Project GDYCSZ201469.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Guilin University of Electronic Technology, Guilin, 541004, Guangxi, China

    Guoyong Cai, Liyuan Wang & Haiyang He

Authors
  1. Guoyong Cai
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  2. Liyuan Wang
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  3. Haiyang He
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Corresponding author

Correspondence to Guoyong Cai .

Editor information

Editors and Affiliations

  1. Chinese Academy of Sciences, Beijing, China

    Wenjia Niu

  2. Deakin University, Burwood, Victoria, Australia

    Gang Li

  3. Beijing Jiaotong University, Beijing, China

    Jiqiang Liu

  4. Chinese Academy of Sciences, Beijing, China

    Jianlong Tan

  5. Chinese Academy of Sciences, Beijing, China

    Li Guo

  6. Beijing Jiaotong University, Beijing, China

    Zhen Han

  7. Fac. Science&Technology, Deakin University, Burwood, Victoria, Australia

    Lynn Batten

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Cai, G., Wang, L., He, H. (2015). Trust Prediction Based on Interactive Relations Strength. In: Niu, W., et al. Applications and Techniques in Information Security. ATIS 2015. Communications in Computer and Information Science, vol 557. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48683-2_17

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  • DOI: https://doi.org/10.1007/978-3-662-48683-2_17

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-48682-5

  • Online ISBN: 978-3-662-48683-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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