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Instances transformation method based on semantic web for completing data sources

机译:基于语义网的实例转换方法以完成数据源

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Availability at large-scale semantic web data can be considered as an opportunity to be used in data source analysis. This analysis process might not obtain data as required since the data is extracted from external sources. This incompleteness of data source can affect analysis result. To resolve this problem, this paper proposed a method for generating data from a transformation process that built based on semantic web technology (ontologies). The application will apply an algorithm that can find a superclass and a subclass of superclass ontology, by mapping the instances of relevant object property to the ontology classes. The classes are then added to the source as a data object instances. In the mapping process, the data is represented by using semi structured format RDF (Resource Description Framework). Data instances generated from this mapping process will complete the semantic data sources and then support the analysis process.
机译:大规模语义Web数据的可用性可以被视为在数据源分析中使用的机会。由于数据是从外部来源提取的,因此此分析过程可能无法获得所需的数据。数据源的不完整会影响分析结果。为了解决这个问题,本文提出了一种从基于语义Web技术(本体)构建的转换过程中生成数据的方法。该应用程序将应用一种算法,该算法通过将相关对象属性的实例映射到本体类来查找超类本体的超类和子类。然后将这些类作为数据对象实例添加到源中。在映射过程中,使用半结构化格式RDF(资源描述框架)表示数据。从该映射过程生成的数据实例将完成语义数据源,然后支持分析过程。

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