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Information granularity, big data, and computational intelligence

The 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 gat...

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Detalles Bibliográficos
Autores principales: Pedrycz, Witold, Chen, Shyi-Ming
Lenguaje:eng
Publicado: Springer 2015
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-08254-7
http://cds.cern.ch/record/1968763
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author Pedrycz, Witold
Chen, Shyi-Ming
author_facet Pedrycz, Witold
Chen, Shyi-Ming
author_sort Pedrycz, Witold
collection CERN
description The 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.   
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spelling cern-19687632021-04-21T20:49:49Zdoi:10.1007/978-3-319-08254-7http://cds.cern.ch/record/1968763engPedrycz, WitoldChen, Shyi-MingInformation granularity, big data, and computational intelligenceEngineeringThe 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.   Springeroai:cds.cern.ch:19687632015
spellingShingle Engineering
Pedrycz, Witold
Chen, Shyi-Ming
Information granularity, big data, and computational intelligence
title Information granularity, big data, and computational intelligence
title_full Information granularity, big data, and computational intelligence
title_fullStr Information granularity, big data, and computational intelligence
title_full_unstemmed Information granularity, big data, and computational intelligence
title_short Information granularity, big data, and computational intelligence
title_sort information granularity, big data, and computational intelligence
topic Engineering
url https://dx.doi.org/10.1007/978-3-319-08254-7
http://cds.cern.ch/record/1968763
work_keys_str_mv AT pedryczwitold informationgranularitybigdataandcomputationalintelligence
AT chenshyiming informationgranularitybigdataandcomputationalintelligence