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    基于服务调用特征模式的个性化Web服务QoS预测方法

    A Personalized Web Service Quality Prediction Approach Based on Invoked Feature Model

    • 摘要: 随着网络上完成相同功能的Web服务数量不断增长,服务使用者在选择服务之前,通常需要根据服务的历史使用信息对未使用过的服务质量进行预测.考虑到调用时刻用户输入、网络环境及服务运行环境的差异,提出了一种基于服务调用特征模式的个性化QoS预测方法.该方法通过对服务的历史使用信息进行分析,抽取出服务的常用调用特征模式,当用户调用某服务时,根据用户调用服务时特征,找到其对应的调用模式,若在该模式下有使用信息则直接返回给用户;若没有则根据模式的相似度,采用协作过滤算法为其进行预测.实验结果表明该方法可以显著提高Web服务质量预测的准确性,并且效率较高.

       

      Abstract: With the number of Web services increasing exponentially, many Web services available have very similar functionality. One approach to identify the most suitable services for a user is to evaluate the QoS of these services. A personalized QoS prediction method is proposed which exploits network, server environment and user input. It analyzes users’ previous behaviors on the Web and extracts the service invoked feature patterns, and then predicts QoS through the information under the invoked feature patterns and user invoking features. Experimental results show that the proposed method can improve the accuracy of the QoS prediction significantly.

       

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