A reputation system for peer-to-peer networks
NOSSDAV '03 Proceedings of the 13th international workshop on Network and operating systems support for digital audio and video
Trust and Reputation Model in Peer-to-Peer Networks
P2P '03 Proceedings of the 3rd International Conference on Peer-to-Peer Computing
WSDL-Based Automatic Test Case Generation for Web Services Testing
SOSE '05 Proceedings of the IEEE International Workshop
A Mobile Agent-Supported Web Services Testing Platform
EUC '08 Proceedings of the 2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing - Volume 02
Reputation Bootstrapping for Trust Establishment among Web Services
IEEE Internet Computing
Reputation Propagation in Composite Services
ICWS '09 Proceedings of the 2009 IEEE International Conference on Web Services
User-Perceived Service Availability: A Metric and an Estimation Approach
ICWS '09 Proceedings of the 2009 IEEE International Conference on Web Services
Evaluating rater credibility for reputation assessment of web services
WISE'07 Proceedings of the 8th international conference on Web information systems engineering
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Trustworthiness is a synthetic characteristic of Web services, which not only involves objective attributes of software quality, but also subjective perception of users. However accurate assessment for service trustworthiness from user's perception is a difficult problem, since user perception of a particular Web service varies in terms of users, application scenarios and time. In this paper, we present a user oriented Web service trustworthiness assessment approach based on collecting and aggregating user feedbacks. The difference from other research work is that in our approach we consider application and user specific factors including the similarity between contexts of the evaluator and feedback reporter, the timeliness of feedback and the evaluator's preferences on quality properties of a Web service. A prototype of our approach is implemented based on ServiceXchange, a Web service repository and search engine developed by our research team. Experimental results demonstrate that our approach has a significant advantage over other approaches that treat feedbacks equally and ignore the difference among user preferences.