Enriching non-taxonomic relations extracted from domain texts

N. Nabila, Ali Mamat, M. Azmi-Murad, N. Mustapha
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引用次数: 5

Abstract

Extracting non-taxonomic relations is one of the important tasks in the construction of ontology from the text. Most of current methods on identification and extraction of non-taxonomic relations is based on predicate representing relationships between two concepts, namely the relation between subject and object that occurs in a sentence. However, the number of relations that has been identified does not properly represent the domain as the methods only identify a portion of the total relations from domain texts. In this paper, we present a method that increases the number of relations extracted and thus properly represent the domain. In this method, all potential relations are first generated and then less significant ones, based on their frequency, are removed. The method has been tested on a collection of texts that described electronic voting machine and the result is encouraging.
丰富从领域文本中提取的非分类关系
从文本中提取非分类关系是构建本体的重要任务之一。目前大多数非分类关系的识别和提取方法都是基于表示两个概念之间关系的谓词,即句子中出现的主语和宾语之间的关系。然而,已识别的关系数量并不能正确地表示域,因为这些方法只能从域文本中识别总关系的一部分。在本文中,我们提出了一种方法,增加了提取关系的数量,从而正确地表示领域。在这种方法中,首先生成所有潜在的关系,然后根据其频率去除不太重要的关系。该方法已经在一组描述电子投票机的文本上进行了测试,结果令人鼓舞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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