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Web Service Clustering Using Text Mining Techniques

机译:使用文本挖掘技术的Web服务集群

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The idea of a decentralised, self-organising service-oriented architecture seems to be more and more plausible than the traditional registry-based ones in view of the success of the web and the reluctance in taking up web service technologies. Automatically clustering Web Service Description Language (WSDL) files on the web into functionally similar homogeneous service groups can be seen as a bootstrapping step for creating a service search engine and, at the same time, reducing the search space for service discovery. This paper proposes techniques to automatically gather, discover and integrate features related to a set of WSDL files and cluster them into naturally occurring service groups. Despite the lack of a common platform for assessing the performance of web service cluster discovery, our initial experiments using real-world WSDL files demonstrated the great potential of the proposed techniques.
机译:鉴于Web的成功和不愿采用Web服务技术的观点,与传统的基于注册表的架构相比,去中心化,自组织的面向服务的体系结构的想法似乎越来越合理。将Web上的Web服务描述语言(WSDL)文件自动聚集到功能相似的同类服务组中,可以看作是创建服务搜索引擎的引导步骤,同时减少了用于发现服务的搜索空间。本文提出了自动收集,发现和集成与一组WSDL文件有关的功能,并将它们聚集到自然出现的服务组中的技术。尽管缺少用于评估Web服务群集发现性能的通用平台,但我们使用实际WSDL文件进行的初始实验证明了所提出技术的巨大潜力。

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