Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/8788
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dc.contributor.authorLi, M-
dc.contributor.authorAl-Raweshidy, H-
dc.contributor.authorMousavi, A-
dc.contributor.authorQi, M-
dc.date.accessioned2014-07-28T15:46:11Z-
dc.date.available2014-07-28T15:46:11Z-
dc.date.issued2012-
dc.identifier.citationIEEE Transactions on Systems, Man and Cybernetics, Part C: Applications and Reviews, 42(6), 1600 - 1612, 2012en_US
dc.identifier.issn1094-6977-
dc.identifier.urihttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6392460en
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/8788-
dc.descriptionThis is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en_US
dc.description.abstractOntology alignment facilitates exchange of knowledge among heterogeneous data sources. Many approaches to ontology alignment use multiple similarity measures to map entities between ontologies. However, it remains a key challenge in dealing with uncertain entities for which the employed ontology alignment measures produce conflicting results on similarity of the mapped entities. This paper presents OARS, a rough-set based approach to ontology alignment which achieves a high degree of accuracy in situations where uncertainty arises because of the conflicting results generated by different similarity measures. OARS employs a combinational approach and considers both lexical and structural similarity measures. OARS is extensively evaluated with the benchmark ontologies of the ontology alignment evaluation initiative (OAEI) 2010, and performs best in the aspect of recall in comparison with a number of alignment systems while generating a comparable performance in precision.en_US
dc.languageEnglish-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectKnowledge engineeringen_US
dc.subjectOntology alignmenten_US
dc.subjectRough setsen_US
dc.subjectSemantic interoperabilityen_US
dc.subjectSemantic matchingen_US
dc.titleDealing with uncertain entities in ontology alignment using rough setsen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1109/TSMCC.2012.2209869-
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Appears in Collections:Electronic and Computer Engineering
Dept of Electronic and Computer Engineering Research Papers

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