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2014 Volume 29
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RESEARCH ARTICLE   Open Access    

Taxonomy of reputation assessment in peer-to-peer systems and analysis of their data retrieval

  • Information & Computer Science Department

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  • Abstract: The need for reputation assessment is particularly strong in peer-to-peer (P2P) systems because the peers’ personal site autonomy is amplified by the inherent technological decentralization of the environment. However, the decentralization notion makes the problem of designing a P2P-based reputation assessment substantially harder in P2P networks than in centralized settings. Existing reputation systems tackle the reputation assessment process in an ad hoc manner. There is no systematic and coherent way to derive measures and analyze the current reputation systems. In this paper, we propose a reputation assessment process and use it to classify the existing reputation systems. Simulation experiments are conducted and focused on the different methods in selecting the recommendation sources and collecting the recommendations. These two phases can contribute significantly to the overall performance owing to precision, recall, and communication cost.
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  • Cite this article

    Farag Azzedin. 2014. Taxonomy of reputation assessment in peer-to-peer systems and analysis of their data retrieval. The Knowledge Engineering Review 29(4)463−483, doi: 10.1017/S0269888914000174
    Farag Azzedin. 2014. Taxonomy of reputation assessment in peer-to-peer systems and analysis of their data retrieval. The Knowledge Engineering Review 29(4)463−483, doi: 10.1017/S0269888914000174
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RESEARCH ARTICLE   Open Access    

Taxonomy of reputation assessment in peer-to-peer systems and analysis of their data retrieval

  • Information & Computer Science Department

  • Published online: 03 October 2014
The Knowledge Engineering Review  29,  2014, 29(4): 463−483  |  Cite this article

Abstract: Abstract: The need for reputation assessment is particularly strong in peer-to-peer (P2P) systems because the peers’ personal site autonomy is amplified by the inherent technological decentralization of the environment. However, the decentralization notion makes the problem of designing a P2P-based reputation assessment substantially harder in P2P networks than in centralized settings. Existing reputation systems tackle the reputation assessment process in an ad hoc manner. There is no systematic and coherent way to derive measures and analyze the current reputation systems. In this paper, we propose a reputation assessment process and use it to classify the existing reputation systems. Simulation experiments are conducted and focused on the different methods in selecting the recommendation sources and collecting the recommendations. These two phases can contribute significantly to the overall performance owing to precision, recall, and communication cost.

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    Acknowledgments

    • The authors would like to thank all anonymous reviewers for their valuable and helpful comments, resulting in a significant improvement in the quality of this manuscript. This research is supported by King Fahd University of Petroleum and Minerals under Research Grants IN080430 and FT060028.

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    Cite this article
    Farag Azzedin. 2014. Taxonomy of reputation assessment in peer-to-peer systems and analysis of their data retrieval. The Knowledge Engineering Review 29(4)463−483, doi: 10.1017/S0269888914000174
    Farag Azzedin. 2014. Taxonomy of reputation assessment in peer-to-peer systems and analysis of their data retrieval. The Knowledge Engineering Review 29(4)463−483, doi: 10.1017/S0269888914000174
    shu

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