Automatic Domain-Ontology Relation Extraction from Semi-structured Texts

Cheng Xiao, Dequan Zheng, Yuhang Yang, G. Shao
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引用次数: 6

Abstract

This paper presents a new method to acquire Domain-Ontology relations from semi-structured data sources. First, obtain Web documents according to the co-occurrence of concept instance and attribute value. Further, define formats of relation patterns, and extract pattern instances from Web documents, including pattern clustering and pattern combining in each cluster. Finally, relation pattern instances are applied to gain attribute values of new concept instances in Domain-Ontology. Experiments are carried out in the field of film, the rate of pattern incorrect-division and pattern leakage are respectively 0.19% and 1.31%, the highest precision of combined relation patterns reaches 85%. Experimental results demonstrate that the method developed in this paper is fairly efficient.
半结构化文本领域本体关系自动提取
提出了一种从半结构化数据源中获取领域-本体关系的新方法。首先,根据概念实例与属性值的共现性获取Web文档。此外,定义关系模式的格式,并从Web文档中提取模式实例,包括模式集群和每个集群中的模式组合。最后,利用关系模式实例获取领域本体中新概念实例的属性值。在胶片领域进行了实验,模式分割错误率和模式泄漏率分别为0.19%和1.31%,组合关系模式的最高精度达到85%。实验结果表明,本文提出的方法是相当有效的。
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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