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001			84997
003			ES-MaUEC
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007			cr nn 008mamaa
008			160323s2016 gw | s |||| 0|eng d
020			_a9783319241067
040			_aES-MaUEC
050		4	_aQA76.9.D3 _bB385 2016
082	0	4	_a005.74
100	1		_aBatini, Carlo. _913544 _0comprobar BNE19971596528
245	1	0	_aData and Information Quality : _bDimensions, Principles and Techniques _cby Carlo Batini, Monica Scannapieco
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XXVIII, 500 páginas) _b260 ilustraciones, 53 ilustraciones en color
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aData-Centric Systems and Applications _x2197-9723
505	0		_aIntroduction to Information Quality -- Data Quality Dimensions -- Information Quality Dimensions for Maps and Texts -- Data Quality Issues in Linked open data -- Quality Of Images -- Models for Information Quality -- Activities for Information Quality -- Object Identification -- Recent Advances in Object Identification -- Data Quality Issues in Data Integration Systems -- Information Quality in Use -- Methodologies for Information Quality Assessment and Improvement -- Information Quality in Healthcare -- Quality of Web Data and Quality of Big Data: Open Problems -- References -- Index.
520	3		_aThis book provides a systematic and comparative description of the vast number of research issues related to the quality of data and information. It�does so by delivering a sound, integrated and comprehensive overview of the state of the art and future development of data and information quality in databases and information systems. To this end, it presents an extensive description of the techniques that constitute the core of data and information quality research, including record linkage (also called object identification), data integration, error localization and correction, and examines the related techniques in a comprehensive and original methodological framework. Quality dimension definitions and adopted models are also analyzed in detail, and differences between the proposed solutions are highlighted and discussed. Furthermore, while systematically describing data and information quality as an autonomous research area, paradigms and influences deriving from other areas, such as probability theory, statistical data analysis, data mining, knowledge representation, and machine learning are also included. Last not least, the book also highlights very practical solutions, such as methodologies, benchmarks for the most effective techniques, case studies, and examples. The book has been written primarily for researchers in the fields of databases and information management�or in natural sciences who are inte rested in investigating properties ofdata and information that have an impact on the quality of experiments, processes and on real life. The material presented is also sufficiently self-contained for masters or PhD-level courses, and it covers all the fundamentals and topics without the need for other textbooks. Data and information system administrators and practitioners, who deal with systems exposed to data-quality issues and as a result need a systematization of the field and practical methods in the area, will also benefit from the combination of concrete practical approaches with sound theoretical formalisms.
710	2		_aSpringerLink (Online service) _0Local _9106996
942			_2lcc _cLE
988			_aEBOOK, asignarmaterias , EBSPRINGER
650		7	_aGestión del conocimiento _9157801 _0comprobar BNE20003984217 _2embne
650	0	7	_aInformática médica _0 _2embne _9421154
700	1		_aScannapieco, Monica. _997635 _0Local
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-24106-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319241067
907			_a.b12942753 _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b - - _cm _dz _e- _feng _ggw _h0
945			_aQA76.9.D3 B385 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11587040 _z06-04-17
999			_c84997 _d84997 _x1