Mountasser, I. and Ouhbi, B. and Frikh, B. (2016) Hybrid large-scale ontology matching strategy on big data environment. In: UNSPECIFIED.

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Ontology matching is one of the essential methodologies to overcome heterogeneity issues. Multiple knowledge-based and information systems perform ontology matching strategies to find correspondences between several ontologies for the purpose of discovering valuable information across various domains. The design and implementation of matching systems raises several challenges, especially, the matching accuracy and the performance issues. Accordingly, adapting the system to the requirements of Big Data era brings additional perspectives and challenges. Furthermore, to provide on-The-fly matching and intime processing, the system must handle matching accuracy, runtime complexity and performance issues as an entire matching strategy. To this end, this paper presents a new hybrid ontology matching approach that benefit on one hand from the opportunities offered by parallel platforms, and on the other hand from ontology matching techniques, while applying a resourcebased decomposition to improve the performance of the system. © 2016 ACM.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: Information analysis; Information retrieval; Knowledge based systems; Ontology; Web services; Websites, Design and implementations; Heterogeneity resolution; Large-scale ontologies; Ontology matching; Parallel Matching; Parallel platforms; Performance issues; Run time complexity, Big data
Subjects: Computer Science
Divisions: SCIENTIFIC PRODUCTION > Computer Science
Depositing User: Administrateur Eprints Administrateur Eprints
Last Modified: 31 Jan 2020 15:46

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