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    Machine Learning-Based Ontology Mapping Tool to Enable Interoperability in Coastal Sensor Networks

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    etd-09222009-200303.pdf (2.124 Mb )
    Author
    Bheemireddy, Shruthi
    Item Type
    Thesis
    Advisor
    Younan, Nicolas H.
    Durbha, Surya S.
    Committee
    King, Roger L.
    Fowler, James E.
    Metrics
    
    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.
    Degree
    Master of Science
    Major
    Electrical Engineering
    College
    Bagley College of Engineering
    Department
    Department of Electrical and Computer Engineering.
    URI
    https://hdl.handle.net/11668/19385
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    • Theses and Dissertations
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    Mississippi State University Libraries
    395 Hardy Rd
    P.O. Box 5408, Mississippi State, MS 39762-5408
    (662) 325-7668
    (662) 325-0011
    (662) 325-8183
    Contact repository admin Report a problem Terms of use Privacy policy Accessibility MSU Legal
     

     

    Mississippi State University Libraries
    395 Hardy Rd
    P.O. Box 5408, Mississippi State, MS 39762-5408
    (662) 325-7668
    (662) 325-0011
    (662) 325-8183
    Contact repository admin Report a problem Terms of use Privacy policy Accessibility MSU Legal