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Constructing Virtual Documents for Ontology Matching

机译:构造用于本体匹配的虚拟文档

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On the investigation of linguistic techniques used in ontology matching, we propose a new idea of virtual documents to pursue a cost-effective approach to linguistic matching in this paper. Basically, as a collection of weighted words, the virtual document of a URIref declared in an ontology contains not only the local descriptions but also the neighboring information to reflect the intended meaning of the URIref. Document similarity can be computed by traditional vector space techniques, and then be used in the similarity-based approaches to ontology matching. In particular, the RDF graph structure is exploited to define the description formulations and the neighboring operations. Experimental results show that linguistic matching based on the virtual documents is dominant in average F-Measure as compared to other three approaches. It is also demonstrated by our experiments that the virtual documents approach is cost-effective as compared to other linguistic matching approaches.
机译:在对用于本体匹配的语言技术的研究中,我们提出了一种虚拟文档的新思想,以寻求一种经济高效的语言匹配方法。基本上,作为加权词的集合,在本体中声明的URIref的虚拟文档不仅包含本地描述,而且还包含反映URIref预期含义的邻近信息。可以通过传统的向量空间技术来计算文档相似度,然后将其用于基于相似度的本体匹配方法中。特别是,利用RDF图结构来定义描述公式和相邻操作。实验结果表明,与其他三种方法相比,基于虚拟文档的语言匹配在平均F量测中占主导地位。我们的实验还证明,与其他语言匹配方法相比,虚拟文档方法具有成本效益。

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