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首页> 外文期刊>International Journal of Computational Science and Engineering >Isolation-based subsumption reasoning with enormous volume of web ontologies for scalable semantic service discovery
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Isolation-based subsumption reasoning with enormous volume of web ontologies for scalable semantic service discovery

机译:具有大量Web本体的基于隔离的包含推理,可扩展的语义服务发现

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摘要

The description of service with expressive Web Ontology Language (OWL) ontologies facilitates semantics-based service advertisement and discovery. However, modern description logic (DL) reasoners do not provide sufficiently tolerable and scalable infrastructure for the advertisement and discovery of service profiles on the basis of enormous volumes of OWL ontologies on the web. In this paper, we present an import graph-based tolerable and scalable reasoner that can be implemented on top of off-the-shelf DL reasoners. The reasoner has been designed to reduce the reasoning workload of these reasoners by excluding ontologies not relevant for resolving a given subsumption query. On average, the proposed method isolates about 87.6%-99.9% of all ontologies when performing a given reasoning task. This leads to a significant reduction, by at least 85.6%, in the response time of subsumption reasoning when a naive reasoning strategy involving the loading of all ontologies onto a reasoner is used.
机译:具有表现力的Web本体语言(OWL)本体的服务描述有助于基于语义的服务广告和发现。但是,现代的描述逻辑(DL)推理器没有基于网络上的大量OWL本体为广告和服务配置文件的发现提供足够可容忍和可扩展的基础结构。在本文中,我们提出了一种基于导入图的可容忍和可扩展的推理器,该推理器可以在现成的DL推理器之上实现。推理机旨在通过排除与解决给定包含查询无关的本体来减少这些推理机的推理工作量。在执行给定的推理任务时,所提出的方法平均可分离出所有本体的约87.6%-99.9%。当使用将所有本体加载到推理机上的幼稚推理策略时,这将导致包含推理的响应时间显着减少至少85.6%。

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