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A Fuzzy Ontology-Based Semantic Data Integration System

Cristiane A. Yaguinuma (), Gustavo F. Afonso (), Vinícius Ferraz (), Sérgio Borges () and Marilde T. P. Santos ()
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Cristiane A. Yaguinuma: Department of Computer Science, Federal University of São Carlos, Rod. Washington Luís, Km 235, P.O. Box 676, 13565-905 São Carlos – SP – Brazil, Brazil
Gustavo F. Afonso: Department of Computer Science, Federal University of São Carlos, Rod. Washington Luís, Km 235, P.O. Box 676, 13565-905 São Carlos – SP – Brazil, Brazil
Vinícius Ferraz: Department of Computer Science, Federal University of São Carlos, Rod. Washington Luís, Km 235, P.O. Box 676, 13565-905 São Carlos – SP – Brazil, Brazil
Sérgio Borges: Department of Computer Science, Federal University of São Carlos, Rod. Washington Luís, Km 235, P.O. Box 676, 13565-905 São Carlos – SP – Brazil, Brazil
Marilde T. P. Santos: Department of Computer Science, Federal University of São Carlos, Rod. Washington Luís, Km 235, P.O. Box 676, 13565-905 São Carlos – SP – Brazil, Brazil

Journal of Information & Knowledge Management (JIKM), 2011, vol. 10, issue 03, 285-299

Abstract: Data integration becomes even more necessary given the increasing availability of data from distributed and heterogeneous sources. To address such heterogeneity, crisp ontologies have been employed in order to represent the semantics of integrated data. However, it is interesting to use fuzzy logic concepts in these ontologies for a more expressive representation of vague information relevant to some domains. In this context, this paper presents DISFOQuE system for data integration based on fuzzy ontology, which provides a homogeneous view of data sources and also performs query expansions in order to retrieve more comprehensive answers for the user. We have executed a real experiment in the domain of watershed analysis, which provided a homogeneous view of the watershed data sources and more effective answers to researchers.

Keywords: Data Integration; fuzzy ontology; query expansion; semantic information processing (search for similar items in EconPapers)
Date: 2011
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DOI: 10.1142/S0219649211002997

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