000			03674nam a22004215i 4500
999			_c387262 _d387262
001			387262
003			ES-MaUEC
005			20230219111012.0
006			a||||fo|||| 00| 0
007			cr nn 008mamaa
008			220601s2015 sz | s |||| 0|eng d
020			_a9783031018534
024	7		_a10.1007/978-3-031-01853-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.D343 _b2015 EB
100	1		_aDong, Xin Luna, _d1975- _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687017
245	1	0	_aBig Data Integration _cby Xin Luna Dong, Divesh Srivastava
250			_a1st edition 2015
264		1	_aCham _bSpringer International Publishing _c2015
300			_a1 recurso en línea (XX, 178 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		_aPreface -- Acknowledgments -- Getting Started -- From Services to Service Worlds -- The Human Condition -- Service Concepts -- Design and its Limits -- Service Design -- An anthropology of Services -- References -- Author Biographies.
520			_aThe big data era is upon us: data are being generated, analyzed, and used at an unprecedented scale, and data-driven decision making is sweeping through all aspects of society. Since the value of data explodes when it can be linked and fused with other data, addressing the big data integration (BDI) challenge is critical to realizing the promise of big data. BDI differs from traditional data integration along the dimensions of volume, velocity, variety, and veracity. First, not only can data sources contain a huge volume of data, but also the number of data sources is now in the millions. Second, because of the rate at which newly collected data are made available, many of the data sources are very dynamic, and the number of data sources is also rapidly exploding. Third, data sources are extremely heterogeneous in their structure and content, exhibiting considerable variety even for substantially similar entities. Fourth, the data sources are of widely differing qualities, with significant differences in the coverage, accuracy and timeliness of data provided. This book explores the progress that has been made by the data integration community on the topics of schema alignment, record linkage and data fusion in addressing these novel challenges faced by big data integration. Each of these topics is covered in a systematic way: first starting with a quick tour of the topic in the context of traditional data integration, followed by a detailed, example-driven exposition of recent innovative techniques that have been proposed to address the BDI challenges of volume, velocity, variety, and veracity. Finally, it presents merging topics and opportunities that are specific to BDI, identifying promising directions for the data integration community.
988			_aSynthesis Collection of Technology_2015
650		7	_2embne _9495511 _aDatos masivos
650		7	_2embne _9138966 _aBases de datos
700	1		_aSrivastava, Divesh _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687018
776	0	8	_iPrinted edition: _z9783031007255
776	0	8	_iPrinted edition: _z9783031029813
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01853-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _esc _zSI