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QoS-Aware Web Service Recommendation by Collaborative Filtering

机译:协同过滤的QoS感知Web服务推荐

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摘要

With increasing presence and adoption of Web services on the World Wide Web, Quality-of-Service (QoS) is becoming important for describing nonfunctional characteristics of Web services. In this paper, we present a collaborative filtering approach for predicting QoS values of Web services and making Web service recommendation by taking advantages of past usage experiences of service users. We first propose a user-collaborative mechanism for past Web service QoS information collection from different service users. Then, based on the collected QoS data, a collaborative filtering approach is designed to predict Web service QoS values. Finally, a prototype called WSRec is implemented by Java language and deployed to the Internet for conducting real-world experiments. To study the QoS value prediction accuracy of our approach, 1.5 millions Web service invocation results are collected from 150 service users in 24 countries on 100 real-world Web services in 22 countries. The experimental results show that our algorithm achieves better prediction accuracy than other approaches. Our Web service QoS data set is publicly released for future research.
机译:随着万维网上Web服务的出现和采用的增加,服务质量(QoS)对于描述Web服务的非功能特性变得越来越重要。在本文中,我们提出了一种协作过滤方法,用于利用Web服务用户过去的使用经验来预测Web服务的QoS值并提出Web服务推荐。我们首先为过去从不同服务用户收集Web服务QoS信息提出了一种用户协作机制。然后,基于收集的QoS数据,设计了一种协作过滤方法来预测Web服务QoS值。最后,一个名为WSRec的原型由Java语言实现,并部署到Internet上以进行实际实验。为了研究我们方法的QoS值预测准确性,从22个国家/地区的150个服务用户在22个国家/地区的100个真实Web服务中收集了150万个Web服务调用结果。实验结果表明,与其他方法相比,该算法具有更好的预测精度。我们的Web服务QoS数据集已公开发布以供将来研究。

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