A comparative analysis of methodologies for database schema integration
ACM Computing Surveys (CSUR)
Infomaster: an information integration system
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Issues and approaches of database integration
Communications of the ACM
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Data & Knowledge Engineering
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Resolving semantic heterogeneity in schema integration
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DANTE '99 Proceedings of the 1999 International Symposium on Database Applications in Non-Traditional Environments
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IEEE Internet Computing
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The VLDB Journal — The International Journal on Very Large Data Bases
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VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
An adaptive approach to schema classification for data warehouse modeling
Journal of Computer Science and Technology
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ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
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MODELS'12 Proceedings of the 15th international conference on Model Driven Engineering Languages and Systems
International Journal of Advanced Pervasive and Ubiquitous Computing
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Currently, schema integration frameworks use approaches like rule-based, machine learning, etc. This paper presents an ontology-based wrapper-mediator framework that uses both the rule-based and machine learning strategies at the same time. The proposed framework uses global and local ontologies for resolving syntactic and semantic heterogeneity, and XML for interoperability. The concepts in the candidate schemas are merged on the basis of the similarity coefficient, which is calculated using the defined rules and the prior mappings stored in the case-base.