Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
PeerTrust: Supporting Reputation-Based Trust for Peer-to-Peer Electronic Communities
IEEE Transactions on Knowledge and Data Engineering
Discovering the best web service
Proceedings of the 16th international conference on World Wide Web
Adaptive Service Composition in Flexible Processes
IEEE Transactions on Software Engineering
A probabilistic approach to modeling and estimating the QoS of web-services-based workflows
Information Sciences: an International Journal
IEEE Transactions on Software Engineering
Investigating web services on the world wide web
Proceedings of the 17th international conference on World Wide Web
Reputation Bootstrapping for Trust Establishment among Web Services
IEEE Internet Computing
Tisa: Toward Trustworthy Services in a Service-Oriented Architecture
IEEE Transactions on Services Computing
An Approach to Non-functional Property Evaluation of Web Services
ICWS '09 Proceedings of the 2009 IEEE International Conference on Web Services
Towards Web Service selection based on QoS estimation
International Journal of Web and Grid Services
QSSA: A QoS-aware Service Selection Approach
International Journal of Web and Grid Services
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Trusted quality of Web service (QoWS) issue is critical for e-commerce applications. However, many existing studies have little work in situations that have insufficient or no historical information regarding QoWS data. In this study, we propose a trusted QoWS metric approach, that is, Bayesian Approach with Maximum Entropy Principle. The key of our proposed approach is to extract QoWS prior distribution of Web service by using Maximum Entropy Principle and then to infer QoWS posterior distribution of Web service by using Bayesian Approach. On the basis of the obtained QoWS posterior distribution, trusted QoWS can be measured. We conduct extensive simulations to evaluate our proposed approach. The simulation results demonstrate that our proposed approach can obtain trusted QoWS effectively. Copyright © 2012 John Wiley & Sons, Ltd.