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dc.contributor.authorGeesaman, Paul Louis
dc.contributor.otherQueen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.))en
dc.date2014-01-29 14:38:52.873en
dc.date.accessioned2014-01-29T20:04:21Z
dc.date.available2014-01-29T20:04:21Z
dc.date.issued2014-01-29
dc.identifier.urihttp://hdl.handle.net/1974/8593
dc.descriptionThesis (Master, Computing) -- Queen's University, 2014-01-29 14:38:52.873en
dc.description.abstractThe Semantic Web is an endeavour to enhance the web with the ability to represent knowledge. The knowledge is expressed through what are called ontologies. In order to make ontologies useful, it is important to be able to match the knowledge represented in different ontologies. This task is commonly known as ontology alignment. Ontology alignment has been studied, but it remains an open problem with an annual competition dedicated to measure alignment tools' performance. Many alignment tools are computationally heavy, require training, or are useful in a specific field of study. We propose an ontology alignment method, NeCO, that builds on clone detection techniques to align ontologies. NeCO inherits the clone detection features, and it is light-weight, does not require training, and is useful for any ontology.en_US
dc.languageenen
dc.language.isoenen_US
dc.relation.ispartofseriesCanadian thesesen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectOntologyen_US
dc.subjectClone Detectionen_US
dc.subjectNear-missen_US
dc.subjectAlignmenten_US
dc.titleNeCO: Ontology Alignment using Near-miss Clone Detectionen_US
dc.typeThesisen_US
dc.description.degreeMasteren
dc.contributor.supervisorCordy, James R.en
dc.contributor.supervisorZouaq, Amalen
dc.contributor.departmentComputingen


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