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Medical Semantic Question Answering Framework on RDF Data Cubes

机译:RDF数据多维数据集的医学语义问答框架

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In this paper, we have proposed a framework to support the semantic question answering over the RDF data cube that is published according to the Linked Open Data (LOD) principles. As statistical data published all over the Internet there is a need to empowers the nonexperts to query in the form of the natural language. But, the existing question answering system unable to support query on the statistical data in the form of the RDF cube. The current research is motivated by the need of the clinical organizations, who wish to develop a platform for analyzing the clinical data across multiple clinical sites. Linked open data (LOD) provides a support to published statistical data in the form of the RDF cube. Our proposed framework will provide a support to interact in the form of the natural language question answering that will produce the SPARQL query to extract the answer from the RDF data cube. In future, we will develop the benchmark to calculate the accuracy of the answer.
机译:在本文中,我们提出了一个框架来支持根据链接的开放数据(LOD)原理发布的RDF数据多维数据集上的语义问题回答。随着统计数据遍及Internet的发布,需要授权非专家以自然语言的形式进行查询。但是,现有的问答系统无法支持以RDF多维数据集的形式对统计数据进行查询。当前的研究是由临床组织的需求所推动的,他们希望开发一个平台来分析多个临床站点的临床数据。链接开放数据(LOD)以RDF多维数据集的形式提供对已发布统计数据的支持。我们提出的框架将以自然语言问答的形式提供交互支持,这将产生SPARQL查询以从RDF数据多维数据集中提取答案。将来,我们将开发基准来计算答案的准确性。

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