Uncertain schema matching

by Gal, Avigdor

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Title Statements

Full title :Uncertain schema matching / Avigdor Gal.

Summary

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.

Edition Statements

Publication Date:©2011.

Publication Statements

Publisher(s):Springer
Place of Publication:Cham, Switzerland
Language:eng
Publication Date:©2011.

Notes

Series from website.

The Physical Object

Description:1 online resource (xii, 85 pages) : : illustrations

Edition Identifiers

ISBN:9781608454341, 1608454347, 1608454339, 9781608454334, 9783031018459, 3031018451
DOI:10.1007/978-3-031-01845-9
oclc:ocn708649889
LC Classification:QA76.9.D338
Dewey Decimal:005.73

1. Introduction -- Schema matching in the data integration life cycle -- Manuscript outline.

2. Models of uncertainty -- Probability theory -- Fuzzy set theory -- Triangular norms -- Fuzzy aggregate operators -- Discussion.

3. Modeling uncertain schema matching -- Model -- Schema and attributes -- Attribute correspondences and the similarity matrix -- Schema matching -- (Yet another) schema matcher classification -- Model usage -- Deep web information -- Semantic matching -- Holistic matching -- Non-(1 : 1) cardinality constraints -- Reasoning with uncertain schema matching -- Reasoning using fuzzy set theory -- Reasoning using probability theory -- Assessing matching quality -- The monotonicity principle.

4. Schema matcher ensembles -- The art of matcher ensembling -- 2LNB: a voting mechanism for ensembles -- Constructing ensembles -- AdaBoost -- SMB: schema matcher boosting -- Ensemble construction with SMB: empirical analysis.

5. Top-K schema matchings -- Top-K schema matchings: definition -- Algorithms for identifying top-K matchings -- Finding the top-2 matchings using Abest -- Finding the top-2 matchings using alternating paths -- Finding the top-K matchings -- Extending…

Subjects

Appariement (Statistique) COMPUTERS -- Data Processing Data integration (Computer science) Incertitude (Théorie de l'information) Intégration de données (Informatique) Statistical matching Uncertainty (Information theory)