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Discovering Semantic Associations Among Web Services Based On The Qualitative Probabilistic Network

机译：基于定性概率网络发现Web服务之间的语义关联

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摘要

In recent years, the intelligent management and decision of Web services have attracted more and more attention due to the wide applications in various aspects of the real world. With the increase of Web services in an organization, the desired on-line services should be located rapidly requiring not only the syntactic but also the semantic techniques. In addition, aiming at fulfilling complex applications by discovering and composing available services automatically and precisely, it is indispensable to develop an underlying model and the corresponding measure for semantic associations among given Web services. In this paper, by mining the historical invocations of component services, we first construct a semantic model to describe their behavior rules based on the qualitative probabilistic network. Further, we propose a distance measure and the approach to discovering semantic associations among Web services. Preliminary experiments and performance studies show that our methods are feasible. Moreover, high recall and precision can be achieved when our methods are applied to Web service search.
机译：近年来，由于在现实世界中各个方面的广泛应用，Web服务的智能管理和决策受到越来越多的关注。随着组织中Web服务的增加，所需的在线服务应迅速定位，不仅需要语法，而且还需要语义技术。另外，为了通过自动和精确地发现和组合可用的服务来满足复杂的应用程序，为给定的Web服务之间的语义关联开发一个基础模型和相应的方法是必不可少的。在本文中，通过挖掘组件服务的历史调用，我们首先构建了一个基于定性概率网络的语义模型来描述它们的行为规则。此外，我们提出了一种距离度量和发现Web服务之间语义关联的方法。初步实验和性能研究表明，我们的方法是可行的。此外，将我们的方法应用于Web服务搜索时，可以实现较高的查全率和准确性。

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