Subjective Trust Inference in Composite Services

Authors

  • Lei Li Macquarie University
  • Yan Wang Macquarie University

DOI:

https://doi.org/10.1609/aaai.v24i1.7504

Keywords:

Composite services, Trust evaluation, Subjective probability

Abstract

In Service-Oriented Computing (SOC) environments, the trustworthiness of each service is critical for a service client when selecting one from a large pool of services. The trust value of a service is usually in the range of [0,1] and is evaluated from the ratings given by service clients, which represent the subjective belief of these service clients on the satisfaction of delivered services. So a trust value can be taken as the subjective probability, with which one party believes that another party can perform an action in a certain situation. Hence, subjective probability theory should be adopted in trust evaluation. In addition, in SOC environments, a service usually invokes other services offered by different service providers forming a composite service. Thus, the global trust of a composite service should be evaluated based on complex invocation structures. In this paper, firstly, based on Bayesian inference, we propose a novel method to evaluate the subjective trustworthiness of a service component from a series of ratings given by service clients. Secondly, we interpret the trust dependency caused by service invocations as conditional probability, which is evaluated based on the subjective trust values of service components. Furthermore, we propose a joint subjective probability method to evaluate the subjective global trust of a composite service on the basis of trust dependency. Finally, we introduce the results of our conducted experiments to illustrate the properties of our proposed subjective global trust inference method.

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Published

2010-07-05

How to Cite

Li, L., & Wang, Y. (2010). Subjective Trust Inference in Composite Services. Proceedings of the AAAI Conference on Artificial Intelligence, 24(1), 1377-1384. https://doi.org/10.1609/aaai.v24i1.7504