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Web Services Reputation Evaluation Model Based on QoS and User Recommendation

Author: LvFuJun
Tutor: ShenLiMin
School: Yanshan University
Course: Computer Software and Theory
Keywords: Web Services Quality of service Users recommend Service reputation Evaluation of credibility Recommended platform
CLC: TP393.09
Type: Master's thesis
Year: 2010
Downloads: 79
Quote: 0
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Abstract


1999 , Microsoft proposed a press conference in San Francisco for the first time the concept of \However , the Web service two camps Microsoft and IBM only from the technical aspects of the development platform and communication protocol , they did not in the Web services to select and recommend the right solution is given . Therefore , this article will QoS and user recommended as the basis of proposed computational model of a Web service reputation , and so recommended for users with the best service . First , we summarize the Web service reputation assessment of the status quo , the basic idea of the existing models and features , induction model strengths and weaknesses . Second, the existing registry Web service QoS lack of credibility , to extend the traditional Web services conceptual model and design service monitoring center . Proposed QoS data provided by the service providers and monitor the QoS data collected QoS update mechanism , the introduction of the time decay thinking , updated by the weighted sum method for QoS in order to improve the service QoS credibility . Again , the definition of the preferences similar users may be recommended user , the user evaluate the credibility of related concepts such as integrated services QoS and user experience feedback given Web service reputation evaluation model . Quantitative model calculation based on QoS service QoS integrated value , using the Pearson correlation coefficient to identify a set of evaluation of similar users , calculated based on the the evaluation similarity evaluation value of the group of users users recommend using QoS integrated value and user recommended calculation Web service credibility, and select the best Web services based on Web service reputation . In addition, for the problem of malicious recommendations given the user evaluation Credits calculation method . Finally, the the QoS update mechanism using the proposed service reputation evaluation model and the collaborative filtering technology to achieve a Web service recommendation platform , the platform can be recommended differences in user experience and provide users with a service test tool . The examples demonstrate the feasibility and availability of the model .

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