A Scalable Probabilistic Approach to Trust Evaluation

  • Xiaoqing Zheng
  • Zhaohui Wu
  • Huajun Chen
  • Yuxin Mao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3986)


The Semantic Web will only achieve its full potential when users have trust in its operations and in the quality of services and information provided, so trust is inevitably a high-level and crucial issue. Modeling trust properly and exploring techniques for establishing computational trust is at the heart of the Semantic Web to realize its vision. We propose a scalable probabilistic approach to trust evaluation which combines a variety of sources of information and takes four types of costs (operational, opportunity, service charge and consultant fee) and utility into consider during the process of trust evaluation. Our approach gives trust a strict probabilistic interpretation which can assist users with making better decisions in choosing the appropriate service providers according to their preferences. A formal robust analysis has been made to examine the performance of our method.


Posterior Distribution Trust Model MultiAgent System Average Precision Trust Evaluation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xiaoqing Zheng
    • 1
  • Zhaohui Wu
    • 1
  • Huajun Chen
    • 1
  • Yuxin Mao
    • 1
  1. 1.College of Computer ScienceZhejiang UniversityHangzhouChina

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