000 03473nam a22005775i 4500
001 978-3-319-27520-8
003 DE-He213
005 20220801215338.0
007 cr nn 008mamaa
008 160205s2016 sz | s |||| 0|eng d
020 _a9783319275208
_9978-3-319-27520-8
024 7 _a10.1007/978-3-319-27520-8
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aTechniques and Environments for Big Data Analysis
_h[electronic resource] :
_bParallel, Cloud, and Grid Computing /
_cedited by B. S.P. Mishra, Satchidananda Dehuri, Euiwhan Kim, Gi-Name Wang.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXI, 191 p. 103 illus., 76 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,
_x2197-6511 ;
_v17
505 0 _aIntroduction to Big Data Analysis -- Parallel Environments -- A Deep Dive into the Hadoop World to Explore its Various Performances -- Natural Language Processing and Machine Learning for Big Data -- Big Data and Cyber Foraging: Future Scope and Challenges -- Parallel GA in Big Data Analysis -- Evolutionary Algorithm Based Techniques to Handle Big Data -- Statistical and Evolutionary Feature Selection Techniques Parallelized using MapReduce Programming Model -- A Data Aware Scheme for Scheduling Big-Data Applications on SAVANNA Hadoop -- The Role of Grid Technologies: A Next Level Combat with Big Data.
520 _aThis volume is aiming at a wide range of readers and researchers in the area of Big Data by presenting the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chapters providing a concise introduction to Big Data Analysis and recent Techniques and Environments for Big Data Analysis. It gives insight into how the expensive fitness evaluation of evolutionary learning can play a vital role in big data analysis by adopting Parallel, Grid, and Cloud computing environments.
650 0 _aComputational intelligence.
_97716
650 0 _aData mining.
_93907
650 0 _aArtificial intelligence.
_93407
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aData Mining and Knowledge Discovery.
_943799
650 2 4 _aArtificial Intelligence.
_93407
700 1 _aMishra, B. S.P.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_943800
700 1 _aDehuri, Satchidananda.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_943801
700 1 _aKim, Euiwhan.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_943802
700 1 _aWang, Gi-Name.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_943803
710 2 _aSpringerLink (Online service)
_943804
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319275185
776 0 8 _iPrinted edition:
_z9783319275192
776 0 8 _iPrinted edition:
_z9783319801605
830 0 _aStudies in Big Data,
_x2197-6511 ;
_v17
_943805
856 4 0 _uhttps://doi.org/10.1007/978-3-319-27520-8
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c77386
_d77386