Jsontoonto: Building Owl2 Ontologies From Json Documents

Sara Sbai, Mohammed Reda Chbihi Louhdi,Hicham Behja, Rabab Chakhmoune

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS(2019)

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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.
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关键词
JSON documents, OWL2 ontologies, ontology generation, transformation rules, information theory, classification, decision trees
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