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Customizable Web services matching and ranking tool:implementation and evaluation

机译:可定制的Web服务匹配和排名工具:实现和评估

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摘要

The matchmaking is a crucial operation in Web service discovery and selection. The objective of the matchmaking is to discover and select the most appropriate Web service among the different available candidates. Different matchmaking frameworks are now available in the literature but most of them present at least one of the following shortcomings: (i) use of strict syntactic matching; (ii) use of capability-based matching; (iii) lack of customization support; and (iv) lack of accurate ranking of matching Web services. The objective of this paper is thus to present the design, implementation and evaluation of the Parameterized Matching-Ranking Framework (PMRF). The PMRF uses semantic matchmaking, accepts capability and property attributes, supports different levels of customization and generates a ranked list of Web services. Accordingly, it fully overcomes the first, third and fourth shortcomings enumerated earlier and partially addresses the second one. The PMRF is composed of two layers. The role of the first layer is to parse the input data and parameters and then transfer it to the second layer, which represents the matching and ranking engine. The comparison of PMRF to iSeM-logic-based and SPARQLent, using the OWLS-TC4 datasets, shows that the algorithms supported by PMRF outperform those proposed in iSeM-logic-based and SPARQLent.
机译:配对是Web服务发现和选择中的关键操作。配对的目的是在不同的可用候选中发现并选择最合适的Web服务。现在,文献中提供了不同的匹配框架,但其中大多数都至少具有以下缺点之一:(i)使用严格的语法匹配; (ii)使用基于能力的匹配; (iii)缺乏定制支持; (iv)缺乏对匹配Web服务的准确排名。因此,本文的目的是介绍参数化匹配排名框架(PMRF)的设计,实现和评估。 PMRF使用语义匹配,接受功能和属性属性,支持不同级别的自定义并生成Web服务的排名列表。因此,它完全克服了先前列举的第一,第三和第四项缺点,并部分解决了第二项缺点。 PMRF由两层组成。第一层的作用是解析输入数据和参数,然后将其传输到第二层,该第二层代表匹配和排名引擎。使用OWLS-TC4数据集将PMRF与基于iSeM逻辑的SPARQLent进行比较,表明PMRF支持的算法优于基于iSeM逻辑的SPARQLent所提出的算法。

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