Json']JsonToOnto: Building Owl2 Ontologies from Json']Json Documents

被引：0

作者：

Sbai, Sara ^{[1
]}

Chbihi Louhdi, Mohammed Reda ^{[2
]}

Behja, Hicham ^{[1
]}

Chakhmoune, Rabab ^{[1
]}

机构：

[1] Hassan II Univ, LRI Lab, ENSEM, Casablanca, Morocco

[2] Hassan II Univ, Fac Sci Ain Chock, Res Lab Comp Sci Innovat, Casablanca, Morocco

来源：

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS | 2019年 / 10卷 / 10期

关键词：

!text type='JSON']JSON[!/text] documents; OWL2; ontologies; ontology generation; transformation rules; information theory; classification; decision trees;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The amount of data circulating through the web has grown rapidly recently. This data is available as semi-structured or unstructured documents, especially JSON documents. However, these documents lack semantic description. In this paper, we present a method to automatically extract an OWL2 ontology from a JSON document. We propose a set of transformation rules to transform JSON elements to ontology components. Our approach also allows analyzing the content of JSON documents to discover categorization in order to generate class hierarchy. Finally, we evaluate our approach by conducting experiments on several JSON documents. The results show that the obtained ontologies are rich in terms of taxonomic relationships.

引用

页码：213 / 218

页数：6

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