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Computational Social Networks pp 133–154Cite as

A Reliability-Based Metric for Inferring Trust from Recommendations in Knowledge Sharing Networks

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Abstract

As knowledge sharing on the Web becomes widespread, it becomes more difficult to know the trustworthiness of the knowledge source. Trust and recommendation have been used for inferring the trustworthiness of unknown entities in many different domains. We introduce trust and recommendation in the EKOSS knowledge sharing network to infer the trustworthiness of a knowledge-sharing agent. We present a reliability-based trust metric for generating locally-calculated inferred trust values using recommendations from trusted agents. The effectiveness of our method is demonstrated through simulation experiments on artificially generated social networks. The advantages and disadvantages of using this method on different kinds of Web-based knowledge sharing networks are discussed.

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Acknowledgements

Support for this work was provided by the Knowledge Failure Database project at the Japan Science and Technology Agency, the Alliance for Global Sustainability Promotion Office at University of Tokyo, and the Office of the President of the University of Tokyo.

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Authors and Affiliations

  1. Science Integration Programme (Human), Department of Frontier Sciences and Science Integration, Division of Project Coordination, The University of Tokyo, Kashiwa, 277-8568, Japan

    Weisen Guo & Steven B. Kraines

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  1. Weisen Guo
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  2. Steven B. Kraines
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Correspondence to Weisen Guo .

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  1. Auburn, 98071, USA

    Ajith Abraham

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© 2012 Springer-Verlag London

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Guo, W., Kraines, S.B. (2012). A Reliability-Based Metric for Inferring Trust from Recommendations in Knowledge Sharing Networks. In: Abraham, A. (eds) Computational Social Networks. Springer, London. https://doi.org/10.1007/978-1-4471-4051-1_6

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  • DOI: https://doi.org/10.1007/978-1-4471-4051-1_6

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4050-4

  • Online ISBN: 978-1-4471-4051-1

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