EAN: 9783031007170

Bilder-Quelle: discount24.de - Sport-Freizeit

Schema matching is the task of providing correspondences between concepts describing the meaning of data in various heterogeneous distributed 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 duplicate data elimination or automatic streamlining of workflow activities that involve heterogeneous data sources. Although schema matching research has been ongoing for over 25 years more recently a realization has emerged that schema matchers are inherently uncertain. Since 2003 work on the uncertainty in schema matching has picked up along with research on uncertainty in other areas of data management. This lecture presents various aspects of uncertainty in schema matching within a single unified framework. We introduce basic formulations of uncertainty and provide several alternative representations of schema matching uncertainty. Then we cover two common methods that have been proposed to deal with uncertainty in schema matching namely ensembles and top-K matchings and analyze them in this context. We conclude with a set of real-world applications. Table of Contents: Introduction Models of Uncertainty Modeling Uncertain Schema Matching Schema Matcher Ensembles Top-K Schema Matchings Applications Conclusions and Future Work

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24.03.2025 um 03:18 Uhr

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