使用Jena语义框架和颗粒推理器进行OWL、RDF、RDFS推理派生

Javed Ahmad Khan, Suresh Kumar
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引用次数: 16

摘要

语义网是万维网的延伸。在语义web中,每个资源和服务都借助web本体语言(OWL)进行注释。资源描述框架(RDF)将web信息表示为属性和值。资源描述框架模式(RDFS)将信息资源表示为类,并在这些类的帮助下定义属性。在本文中,我们利用proprosamadg 4.3 alpha工具创建了大学本体。我们提出的信息检索框架,产生的结果具有更好的精度,召回率和信息过量。在Jena语义框架和粒子推理工具的帮助下,我们分析了OWL推理比None、RDF和RDFS提供了更多的相关信息。我们已经开发了五个大学领域本体,但只给出了两个本体的结果。我们已经验证了我们提出的框架为这两个本体提供了更多相关的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
OWL, RDF, RDFS inference derivation using Jena semantic framework & pellet reasoner
Semantic web is an extension of World Wide Web. In Semantic web each resources and services is annotated with the help of web ontology language (OWL). Resource description framework (RDF) represents the web information into its properties and values. Resource description framework schema (RDFS) represents information resources into classes and properties are defined with the help of these classes. In this paper we create university ontology with the help of protégé 4.3 alpha tool. We have proposed information retrieval framework that produce results with better precision, recall and information overkill. With the help of Jena semantic framework and pellet reasoner tools we analyze that OWL inference provide more relevant information compared to None, RDF and RDFS. We have developed five university domain ontologies but presented the result only for two ontologies. We have validated that our proposed framework provide more relevant information for these two ontologies.
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