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020 _a9783319082547
024 7 _a10.1007/978-3-319-08254-7
_2doi
040 _bspa
_dES-MaUEC
050 4 _aQA76.9.S63
_b2015 EB
245 1 0 _aInformation Granularity, Big Data, and Computational Intelligence
_cedited by Witold Pedrycz, Shyi-Ming Chen.
264 1 _aCham
_bSpringer International Publishing
_c2015
300 _a1 recurso en línea (XI, 444 páginas 123 ilustraciones, 26 ilustraciones a color.)
336 _2rdacontent
_aTexto (visual)
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
490 0 _aStudies in Big Data,
_x2197-6503 ;
_v8
490 0 _aEngineering (Springer-11647)
505 0 _aFrom the Contents: Nearest Neighbor Queries on Big Data -- Information Mining for Big Information -- Information Granules Problem: An Efficient Solution of Real-Time Fuzzy Regression Analysis -- How to Understand Connections Based on Big Data: From Cliques to Flexible Granules.
520 3 _aThe recent pursuits emerging in the realm of big data processing, interpretation, collection and organization have emerged in numerous sectors including business, industry, and government organizations. Data sets such as customer transactions for a mega-retailer, weather monitoring, intelligence gathering, quickly outpace the capacities of traditional techniques and tools of data analysis. The 3V (volume, variability and velocity) challenges led to the emergence of new techniques and tools in data visualization, acquisition, and serialization. Soft Computing being regarded as a plethora of technologies of fuzzy sets (or Granular Computing), neurocomputing and evolutionary optimization brings forward a number of unique features that might be instrumental to the development of concepts and algorithms to deal with big data. This carefully edited volume provides the reader with an updated, in-depth material on the emerging principles, conceptual underpinnings, algorithms and practice of Computational Intelligence in the realization of concepts and implementation of big data architectures, analysis, and interpretation as well as data analytics. The book is aimed at a broad audience of researchers and practitioners including those active in various disciplines in which big data, their analysis and optimization are of genuine relevance. One focal point is the systematic exposure of the concepts, design methodology, and detailed algorithms. In general, the volume adheres to the top-down strategy starting with the concepts and motivation and then proceeding with the detailed design that materializes in specific algorithms and representative applications. The material is self-contained and provides the reader with all necessary prerequisites and, augments some parts with a step-by-step explanation of more advanced concepts supported by a significant amount of illustrative numeric material and some application scenarios to motivate the reader and make some abstract concepts more tangible.   .
988 _aEBSPRINGER_2018
650 7 _9166276
_aSoft Computing
650 7 _9495511
_aDatos masivos
700 1 _aPedrycz, Witold
_d1953-
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_1http://viaf.org/viaf/49305507/
_967495
700 1 _aChen, Shyi-Ming
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_0http://id.loc.gov/authorities/names/no2009163507
_1http://viaf.org/viaf/101512796/
_998849
776 0 8 _iEdición impresa:
_z9783319082554
776 0 8 _iEdición impresa:
_z9783319082530
776 0 8 _iEdición impresa:
_z9783319381619
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-08254-7
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _b03/2019
_dz
_eIG
_zSI