Ontology Schema Alignment Method Using Relationship among Ontology Instances and Resources in Linked Open Data 


Vol. 45,  No. 2, pp. 418-427, Feb.  2020
10.7840/kics.2020.45.2.418


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  Abstract

In this paper, we propose a method to perform ontology schema alignment using LOD cloud as external knowledge. To do so, we attempted to align the ontology schema by identifying the relationship between the ontology classes and the instances, the relationship between the instances and the LOD resources, and the hierarchical structure among the LOD resources. We performed one-class clustering using the predicates to find the resources in the LOD cloud that are conceptually related to the instances of the ontology classes. We also determined the LOD resources with the most semantic association with the classes through the similarity calculation based on Latent Semantic Analysis (LSA). In order to prove the superiority of the proposed framework, three ontologies were developed. Experimental results show that the identification of equivalence relationships between ontology classes and resources and the identification of equivalence relationships between heterogeneous ontology classes are excellent.

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  Cite this article

[IEEE Style]

M. Kim, J. Kim, M. Sohn, G. Park, "Ontology Schema Alignment Method Using Relationship among Ontology Instances and Resources in Linked Open Data," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 2, pp. 418-427, 2020. DOI: 10.7840/kics.2020.45.2.418.

[ACM Style]

Minhwan Kim, Jongmo Kim, Mye Sohn, and Gyudong Park. 2020. Ontology Schema Alignment Method Using Relationship among Ontology Instances and Resources in Linked Open Data. The Journal of Korean Institute of Communications and Information Sciences, 45, 2, (2020), 418-427. DOI: 10.7840/kics.2020.45.2.418.

[KICS Style]

Minhwan Kim, Jongmo Kim, Mye Sohn, Gyudong Park, "Ontology Schema Alignment Method Using Relationship among Ontology Instances and Resources in Linked Open Data," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 2, pp. 418-427, 2. 2020. (https://doi.org/10.7840/kics.2020.45.2.418)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880