Titlebook: Uncertain Schema Matching; Avigdor Gal Book 2011 Springer Nature Switzerland AG 2011

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Avigdor Galtabsatz der Periode. In diesem Sinne sieht der Verfasser sehr einleuchtend eine Dynamik des Kaufverhaltens durch die Dynamik der Qualitätserwartung begründet. Das Entscheidungsproblem des Herstellers wird deutlich, indem die ceteris-paribus­ Prämisse aufgehoben wird: Die betrachtete Unternehmung kan

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2153-5418 ed data sources. Schema matching is one of the basic operations required by the process of data and schema integration, and thus has a great effect on its outcomes, whether these involve targeted content delivery, view integration, database integration, query rewriting over heterogeneous sources, du

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Models of Uncertainty,As an introduction to themodeling and handling of uncertainty in schema matching, we first present two common mechanismsfor uncertainty management, namely probability theory and fuzzy set theory. According toMagnani and Montesi [2010], the former is representative of quantitative approaches in schem

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Schema Matcher Ensembles,s,1 which combine different schema matchers that use complementary principles to judge the similarity between concepts.The idea is appealing since an ensemble of complementary matchers can potentially compensate for the weaknesses of any given matcher in the ensemble. Indeed, several studies report

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Applications,certain schema matching within a project on a peer-to-peer data integration system. An application to disaster data management systems is discussed in Section 6.2. Section 6.3 looks at the use of uncertain schema matching in Web service discovery and composition. Finally, communities of knowledge ar

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