Theses and Dissertations

Issuing Body

Mississippi State University

Advisor

Younan, Nicolas H.

Committee Member

Durbha, Surya S.

Committee Member

King, Roger L.

Committee Member

Fowler, James E.

Date of Degree

12-11-2009

Document Type

Graduate Thesis - Open Access

Major

Electrical Engineering

Degree Name

Master of Science

College

James Worth Bagley College of Engineering

Department

Department of Electrical and Computer Engineering

Abstract

In today’s world, ontologies are being widely used for data integration tasks and solving information heterogeneity problems on the web because of their capability in providing explicit meaning to the information. The growing need to resolve the heterogeneities between different information systems within a domain of interest has led to the rapid development of individual ontologies by different organizations. These ontologies designed for a particular task could be a unique representation of their project needs. Thus, integrating distributed and heterogeneous ontologies by finding semantic correspondences between their concepts has become the key point to achieve interoperability among different representations. In this thesis, an advanced instance-based ontology matching algorithm has been proposed to enable data integration tasks in ocean sensor networks, whose data are highly heterogeneous in syntax, structure, and semantics. This provides a solution to the ontology mapping problem in such systems based on machine-learning methods and string-based methods.

URI

https://hdl.handle.net/11668/19385

Comments

semantic web||string distance metrics||machine learning techniques||ontology mapping

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