Redundant instances and incorrect instances detection mechanism in ontology population

Xiaoyun Wang, Jianping Yao, Haochen Wang
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Abstract

With the rapid development of the Internet, many researchers have been focused on ontology knowledge bases updating. Ontology population has played an important role in updating ontology knowledge bases. However, most domestic and foreign scholars focus on the process of ontology population, while neglecting how to detect and eliminate redundant instances and how to detect the results of population. In this paper, we proposed a mechanism based on instance matching algorithm, trying to verify the results of population, we also present an empirical analysis to verify the validity of the method.
本体群体中的冗余实例和错误实例检测机制
随着互联网的快速发展,本体知识库的更新成为众多研究者关注的焦点。本体种群在本体知识库的更新中起着重要的作用。然而,国内外学者大多关注本体种群过程,而忽略了如何检测和消除冗余实例以及如何检测种群结果。本文提出了一种基于实例匹配机制的算法,试图对种群结果进行验证,并给出了实证分析来验证该方法的有效性。
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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