000 04006nam a22005055i 4500
001 978-3-319-08254-7
003 DE-He213
005 20200421111207.0
007 cr nn 008mamaa
008 140714s2015 gw | s |||| 0|eng d
020 _a9783319082547
_9978-3-319-08254-7
024 7 _a10.1007/978-3-319-08254-7
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
245 1 0 _aInformation Granularity, Big Data, and Computational Intelligence
_h[electronic resource] /
_cedited by Witold Pedrycz, Shyi-Ming Chen.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXI, 444 p. 123 illus., 26 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Big Data,
_x2197-6503 ;
_v8
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 _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.   .
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aE-commerce.
650 0 _aComputational intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _ae-Commerce/e-business.
700 1 _aPedrycz, Witold.
_eeditor.
700 1 _aChen, Shyi-Ming.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319082530
830 0 _aStudies in Big Data,
_x2197-6503 ;
_v8
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-08254-7
912 _aZDB-2-ENG
942 _cEBK
999 _c54218
_d54218