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On the Combination of Textual and Semantic Descriptions for Automated Semantic Web Service Classification

机译：文本和语义描述的组合，用于自动语义Web服务分类

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摘要

Semantic Web services have emerged as the solution to the need for automating several aspects related to service-oriented architectures, such as service discovery and composition, and they are realized by combining Semantic Web technologies and Web service standards. In the present paper, we tackle the problem of automated classification of Web services according to their application domain taking into account both the textual description and the semantic annotations of OWL-S advertisements. We present results that we obtained by applying machine learning algorithms on textual and semantic descriptions separately and we propose methods for increasing the overall classification accuracy through an extended feature vector and an ensemble of classifiers.
机译：语义Web服务已经成为解决与面向服务的体系结构相关的多个方面（例如服务发现和组合）的需求的解决方案，并且它们是通过结合语义Web技术和Web服务标准来实现的。在本文中，我们考虑到OWL-S广告的文本描述和语义注释，根据Web服务根据其应用领域自动分类的问题。我们介绍了通过将机器学习算法分别应用于文本和语义描述而获得的结果，并提出了通过扩展特征向量和分类器集合来提高整体分类准确性的方法。

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