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The Scientific World Journal
Volume 2014 (2014), Article ID 617087, 9 pages
Research Article

Reputation Revision Method for Selecting Cloud Services Based on Prior Knowledge and a Market Mechanism

Information Engineering College, Henan University of Science and Technology, Luoyang 471023, China

Received 12 October 2013; Accepted 4 November 2013; Published 17 February 2014

Academic Editors: W. Sun, G. Zhang, and J. Zhou

Copyright © 2014 Qingtao Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The trust levels of cloud services should be evaluated to ensure their reliability. The effectiveness of these evaluations has major effects on user satisfaction, which is increasingly important. However, it is difficult to provide objective evaluations in open and dynamic environments because of the possibilities of malicious evaluations, individual preferences, and intentional praise. In this study, we propose a novel unfair rating filtering method for a reputation revision system. This method uses prior knowledge as the basis of similarity when calculating the average rating, which facilitates the recognition and filtering of unfair ratings. In addition, the overall performance is increased by a market mechanism that allows users and service providers to adjust their choice of services and service configuration in a timely manner. The experimental results showed that this method filtered unfair ratings in an effective manner, which greatly improved the precision of the reputation revision system.