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A multi-matching technique for combining similarity measures in ontology integration


A multi-matching technique for combining similarity measures in ontology integration

Alasoud, Ahmed Khalifa (2009) A multi-matching technique for combining similarity measures in ontology integration. PhD thesis, Concordia University.

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NR63399.pdf - Accepted Version


Ontology matching is a challenging problem in many applications, and is a major issue for interoperability in information systems. It aims to find semantic correspondences between a pair of input ontologies, which remains a labor intensive and expensive task. This thesis investigates the problem of ontology matching in both theoretical and practical aspects and proposes a solution methodology, called multi-matching . The methodology is validated using standard benchmark data and its performance is compared with available matching tools. The proposed methodology provides a framework for users to apply different individual matching techniques. It then proceeds with searching and combining the match results to provide a desired match result in reasonable time. In addition to existing applications for ontology matching such as ontology engineering, ontology integration, and exploiting the semantic web, the thesis proposes a new approach for ontology integration as a backbone application for the proposed matching techniques. In terms of theoretical contributions, we introduce new search strategies and propose a structure similarity measure to match structures of ontologies. In terms of practical contribution, we developed a research prototype, called MLMAR - Multi-Level Matching Algorithm with Recommendation analysis technique, which implements the proposed multi-level matching technique, and applies heuristics as optimization techniques. Experimental results show practical merits and usefulness of MLMAR

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (PhD)
Authors:Alasoud, Ahmed Khalifa
Pagination:xi, 128 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:Ph. D.
Program:Computer Science and Software Engineering
Thesis Supervisor(s):Shiri, N and Haarslev, V
ID Code:976336
Deposited By: Concordia University Library
Deposited On:22 Jan 2013 16:23
Last Modified:18 Jan 2018 17:42
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