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Authors: Rihab Idoudi 1 ; Karim Saheb Ettabaa 2 ; Kamel Hamrouni 3 and Basel Solaiman 2

Affiliations: 1 Université Tunis ElManar and Telecom Bretagne, Tunisia ; 2 Telecom Bretagne, France ; 3 Université Tunis ElManar, Tunisia

ISBN: 978-989-758-187-8

Keyword(s): Fuzzy C-Medoid, Ontology Aligning, Semantic Similarity, Similarity Measures.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Data Engineering ; Enterprise Information Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Engineering and Ontology Development ; Knowledge Management ; Knowledge-Based Systems ; Ontologies and the Semantic Web ; Ontology Engineering ; Society, e-Business and e-Government ; Symbolic Systems ; Web Information Systems and Technologies

Abstract: Recently, several ontologies have been proposed for real life domains, where these propositions are large and voluminous due to the complexity of the domain. Consequently, Ontology Aligning has been attracting a great deal of interest in order to establish interoperability between heterogeneous applications. Although, this research has been addressed, most of existing approaches do not well capture suitable correspondences when the size and structure vary vastly across ontologies. Addressing this issue, we propose in this paper a fuzzy clustering based alignment approach which consists on improving the ontological structure organization. The basic idea is to perform the fuzzy clustering technique over the ontology’s concepts in order to create clusters of similar concepts with estimation of medoids and membership degrees. The uncertainty is due to the fact that a concept has multiple attributes so to be assigned to different classes simultaneously. Then, the ontologies are aligned bas ed on the generated fuzzy clusters with the use of different similarity techniques to discover correspondences between conceptual entities. (More)

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Paper citation in several formats:
Idoudi, R.; Ettabaa, K.; Hamrouni, K. and Solaiman, B. (2016). Fuzzy Clustering based Approach for Ontology Alignment.In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-187-8, pages 594-599. DOI: 10.5220/0005916805940599

@conference{iceis16,
author={Rihab Idoudi. and Karim Saheb Ettabaa. and Kamel Hamrouni. and Basel Solaiman.},
title={Fuzzy Clustering based Approach for Ontology Alignment},
booktitle={Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2016},
pages={594-599},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005916805940599},
isbn={978-989-758-187-8},
}

TY - CONF

JO - Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Fuzzy Clustering based Approach for Ontology Alignment
SN - 978-989-758-187-8
AU - Idoudi, R.
AU - Ettabaa, K.
AU - Hamrouni, K.
AU - Solaiman, B.
PY - 2016
SP - 594
EP - 599
DO - 10.5220/0005916805940599

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