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Comparing similarity combination methods for schema matching

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2010

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Gesellschaft für Informatik e.V.

Zusammenfassung

A recurring manual task in data integration or ontology alignment is finding mappings between complex schemas. In order to reduce the manual effort, many matching algorithms for semi-automatically computing mappings were introduced. In the last decade it turned out that a combination of matching algorithms often improves mapping quality. Many possible combination methods can be found in literature, each promising good result quality for a specific domain of schemas. We introduce the rationale of each strategy shortly. Then we evaluate the most commonly used methods on a number of mapping tasks and try to find the most robust strategy that behaves well across all given tasks.

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Peukert, Eric; Maßmann, Sabine; König, Kathleen (2010): Comparing similarity combination methods for schema matching. INFORMATIK 2010. Service Science – Neue Perspektiven für die Informatik. Band 1. Bonn: Gesellschaft für Informatik e.V.. PISSN: 1617-5468. ISBN: 978-3-88579-269-7. pp. 692-701. Regular Research Papers. Leipzig. 27.09.-1.10.2010

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