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Improving Performance of Web Services Query Matchmaking with Automated Knowledge Acquisition

机译:通过自动知识获取提高Web服务查询匹配的性能

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There is a critical need to design and develop tools that abstract away the fundamental complexity of XML-based Web services specifications and toolkits, and provide an elegant, intuitive, simple, and powerful query-based invocation system to end users. Web services based tools and standards have been designed to facilitate seamless integration and development for application developers. As a result, current implementations require the end user to have intimate knowledge of Web services and related toolkits, and users often play an informed role in the overall Web services execution process. We employ a self-learning mechanism and a set of algorithms and optimizations to match user queries with corresponding operations in Web services. Our system uses Semantic Web concepts and Ontologies in the process of automating Web services matchmaking. We present performance analysis of our system and quantify the exact gains in precision and recall due to the knowledge acquisition algorithms.
机译:迫切需要设计和开发工具,以抽象出基于XML的Web服务规范和工具包的基本复杂性,并向最终用户提供优雅,直观,简单且功能强大的基于查询的调用系统。设计了基于Web服务的工具和标准,以促进应用程序开发人员的无缝集成和开发。结果,当前的实现要求最终用户对Web服务和相关工具包有深入的了解,并且用户通常在整个Web服务执行过程中扮演明智的角色。我们采用一种自学习机制以及一组算法和优化,以将用户查询与Web服务中的相应操作进行匹配。我们的系统在自动进行Web服务配对过程中使用语义Web概念和本体。我们介绍了我们系统的性能分析,并对由于知识获取算法而导致的精确度和召回率进行了精确量化。

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