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003			ES-MaUEC
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007			cr nn 008mamaa
008			220601s2011 sz | s |||| 0|eng d
020			_a9783031018459
024	7		_a10.1007/978-3-031-01845-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.D338 _b2011 EB
100	1		_aGal, Avigdor _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687012
245	1	0	_aUncertain Schema Matching _cby Avigdor Gal
250			_a1st edition 2011
264		1	_aCham _bSpringer International Publishing _c2011
300			_a1 recurso en línea (XII, 85 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Data Management _x2153-5426
505	0		_aIntroduction -- Models of Uncertainty -- Modeling Uncertain Schema Matching -- Schema Matcher Ensembles -- Top-K Schema Matchings -- Applications -- Conclusions and Future Work.
520			_aSchema 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.
988			_aSynthesis Collection of Technology_2011
650		7	_2embne _9150569 _aSistemas de gestión de bases de datos
650		7	_2embne _9667868 _aIncertidumbre (Teoría de la información)
650		7	_2embne _9687013 _aCorrelación (Estadística)
776	0	8	_iPrinted edition: _z9783031007170
776	0	8	_iPrinted edition: _z9783031029738
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01845-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _esc _zSI