基于ar - k均值的电力安全本体半自动构建方法

Dezhi Zhao, Jian Sun, Xiaoyu Chen, Xiaoyong Bo, Mingli Yi, Lin Xia
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引用次数: 0

摘要

在电力安全知识图谱构建过程中的数据建模方面,传统的手工构建电力安全本体的方法存在耗时费力的问题。为此,本文提出了一种基于关联规则(AR)和改进K-means的电力安全本体半自动构建方法。首先,以国家电网公司发布的权威数据《电力安全法规》为数据源,采用BP神经网络对本体概念进行半自动提取;然后通过关联规则和改进的K-means算法半自动提取本体概念之间的层次和非层次关系;最后,利用prot本体编辑器直观地表达了电力安全本体概念、概念与实例之间的关系,改进了电力安全知识图谱的构建。算例分析验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semi-automatic construction method of power safety ontology based on AR-K-means
In terms of data modeling during the construction of the power safety knowledge map, the traditional manual method of constructing the power safety ontology has the problem of time-consuming and labor-intensive. Therefore, a semi-automatic construction method of power safety ontology based on Association Rules (AR) and improved K-means is proposed in this paper. First, according to the authoritative data power safety regulations issued by State Grid Corporation as the data source, the BP neural network is used to semi-automatically extract the ontology concept; Then semi-automatically extract hierarchical and non-hierarchical relationships between ontology concepts through Association Rules and an improved K-means algorithm; Finally, the Protégé ontology editor is used to visually express the power safety ontology concept, the relationship between concepts and examples, and improve the construction of the power safety knowledge graph. The analysis of the calculation examples verifies the effectiveness of the method.
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