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A Web Service QoS Prediction Approach Based on Collaborative Filtering

机译:基于协同过滤的Web服务QoS预测方法

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With the increasing numbers of Web services and service users on World Wide Web, predicting QoS( Quality of Service ) for users will greatly aid service selection and discovery. Due to the different backgrounds and experiences of users, they have different QoS experiences when interacting with the same service. Even two users who have similar experiences on some services can have diverging views when considering other services. This paper proposes an approach to predict QoS. It is based on not only other usersȁ9; QoS experiences, but also the environment factor and user input factor. First bring forwards usage information feature model and calculate the similarity of two users based on the feature model. Then consider not only the historic information, but also environment and usersȁ9; inputs, such as bandwidth and data size. Before calculating the user similarity, select a set of Web services that have the highest degree of similarity with the target service, not all of the services. The missing value can be calculated through the data of similar services. The results of the experiment prove that our approach is feasible and effective.
机译:随着万维网上Web服务和服务用户数量的增加,预测用户的QoS(服务质量)将大大有助于服务的选择和发现。由于用户的背景和经验不同,他们在与同一服务进行交互时具有不同的QoS体验。在考虑其他服务时,即使是两个在某些服务上具有类似经验的用户也可能有不同的看法。本文提出了一种预测QoS的方法。它不仅基于其他用户ȁ9,而且还基于其他用户。 QoS体验,还有环境因素和用户输入因素。首先提出使用信息特征模型,并基于该特征模型计算两个用户的相似度。然后不仅要考虑历史信息,还要考虑环境和用户ȁ9;输入,例如带宽和数据大小。在计算用户相似度之前,请选择一组与目标服务而非所有服务具有最高相似度的Web服务。可以通过类似服务的数据来计算缺失值。实验结果证明了该方法的可行性和有效性。

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