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Domain-Specific Inter-textual Non-taxonomic Extraction (DSINTE)

机译:特定领域的跨文本非分类提取(DSINTE)

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Non-taxonomic relation is one of the most important components in ontology to describe a domain. Currently, most studies focused on extracting non-taxonomic relationships from text within the scope of single sentence. The predicate between two concepts (i.e. subject and object) that appear in a same sentence is extracted as potential relation. Therefore the number of identified relations is less that what it could be and does not properly represent the domain. In this paper, we introduced a method named Domain-specific Inter-textual nontaxonomic extraction (DSINTE) to extract the non-taxonomic relations between two concepts that appear not only in a single sentence but also in different sentences. The proposed method has been illustrated using a collection of domain texts from New York Times website. Recall metrics have been used to evaluate the results of the experiments.
机译:非分类关系是本体中描述域的最重要组成部分之一。当前,大多数研究集中在从单句范围内的文本中提取非分类关系。出现在同一句子中的两个概念(即主语和宾语)之间的谓词被提取为潜在关系。因此,已识别关系的数量少于它可能存在的数量,并且不能正确代表该域。在本文中,我们引入了一种称为“领域特定的文本间非分类提取”(DSINTE)的方法,以提取不仅出现在单个句子中而且出现在不同句子中的两个概念之间的非分类关系。已使用《纽约时报》网站上的域文本集说明了所提出的方法。召回指标已用于评估实验结果。

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