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Large-Scale Ontology Alignment- An Extraction Based Method to Support Information System Interoperability

Large-Scale Ontology Alignment- An Extraction Based Method to Support Information System Interoperability

Mourad Zerhouni, Sidi Mohamed Benslimane
Copyright: © 2019 |Volume: 10 |Issue: 2 |Pages: 26
ISSN: 1947-3095|EISSN: 1947-3109|EISBN13: 9781522566816|DOI: 10.4018/IJSITA.2019040104
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MLA

Zerhouni, Mourad, and Sidi Mohamed Benslimane. "Large-Scale Ontology Alignment- An Extraction Based Method to Support Information System Interoperability." IJSITA vol.10, no.2 2019: pp.59-84. http://doi.org/10.4018/IJSITA.2019040104

APA

Zerhouni, M. & Benslimane, S. M. (2019). Large-Scale Ontology Alignment- An Extraction Based Method to Support Information System Interoperability. International Journal of Strategic Information Technology and Applications (IJSITA), 10(2), 59-84. http://doi.org/10.4018/IJSITA.2019040104

Chicago

Zerhouni, Mourad, and Sidi Mohamed Benslimane. "Large-Scale Ontology Alignment- An Extraction Based Method to Support Information System Interoperability," International Journal of Strategic Information Technology and Applications (IJSITA) 10, no.2: 59-84. http://doi.org/10.4018/IJSITA.2019040104

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Abstract

Ontology alignment is an important way of establishing interoperability between Semantic Web applications that use different but related ontologies. Ontology alignment is the process of identifying semantically equivalent entities from multiple ontologies. This is not always obvious because technical constraints such as data volume and execution time are determining factors in the choice of an alignment algorithm. Nowadays, partitioning and modularization are two main strategies for breaking down large ontologies into blocks or ontology modules respectively to align ontologies. This article proposes ONTEM as an effective alignment method for large-scale ontology based on the ontology entities extraction. This article conducts a comprehensive evaluation using the datasets of the OAEI 2018 campaign. The obtained results are promising, and they revealed that ONTEM is one of the most effective systems.

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