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Semantic Mediation in MedPeer: An Ontology-Based Heterogeneous Data Sources Integration System

Semantic Mediation in MedPeer: An Ontology-Based Heterogeneous Data Sources Integration System

Naïma Souâd Ougouti, Haféda Belbachir, Youssef Amghar
Copyright: © 2018 |Pages: 21
ISBN13: 9781522551911|ISBN10: 1522551913|EISBN13: 9781522551928
DOI: 10.4018/978-1-5225-5191-1.ch098
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MLA

Ougouti, Naïma Souâd, et al. "Semantic Mediation in MedPeer: An Ontology-Based Heterogeneous Data Sources Integration System." Information Retrieval and Management: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2018, pp. 2200-2220. https://doi.org/10.4018/978-1-5225-5191-1.ch098

APA

Ougouti, N. S., Belbachir, H., & Amghar, Y. (2018). Semantic Mediation in MedPeer: An Ontology-Based Heterogeneous Data Sources Integration System. In I. Management Association (Ed.), Information Retrieval and Management: Concepts, Methodologies, Tools, and Applications (pp. 2200-2220). IGI Global. https://doi.org/10.4018/978-1-5225-5191-1.ch098

Chicago

Ougouti, Naïma Souâd, Haféda Belbachir, and Youssef Amghar. "Semantic Mediation in MedPeer: An Ontology-Based Heterogeneous Data Sources Integration System." In Information Retrieval and Management: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 2200-2220. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-5191-1.ch098

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Abstract

Peer-to-Peer (P2P) infrastructure is an emerging paradigm that offers new opportunities for the development of large-scale distributed systems. This architecture combined with the new techniques introduced by semantic web as ontologies encouraged the emergence of new multi-source data integration possibilities for sharing information. A challenging problem in such systems is to find correspondences between concepts of their different ontologies. This is a necessary step before locating peers that are relevant with respect to a given query. In this paper, the authors propose a new ontology alignment method which deals with both linguistic and semantic characteristics of concepts and uses graph structure to explore multiple depth levels of neighborhood in calculation of semantic similarity which is the most important part of their global similarity measure. This function is implemented into their new P2P heterogeneous and distributed data integration system MedPeer.

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