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020 _a9783319269894
_9978-3-319-26989-4
024 7 _a10.1007/978-3-319-26989-4
_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 _aBig Data Analysis: New Algorithms for a New Society
_h[electronic resource] /
_cedited by Nathalie Japkowicz, Jerzy Stefanowski.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXII, 329 p. 63 illus., 35 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 ;
_v16
505 0 _aA Machine Learning Perspective on Big Data Analysis -- An Insight on Big Data Analytics -- Toward Problem Solving Support based on Big Data and Domain Knowledge: Interactive Granular Computing and Adaptive Judgment -- An overview of Conceptdrift Applications.- Analysis of Text-Enriched Heterogeneous Information Networks.- Implementing Big Data Analytics Projects in Business -- Data mining in Business: Current Advances and Future Challenges -- Industrial-Scale Ad Hoc Risk Analytics Using MapReduce -- Big Data and the Internet of Things -- Social Network Analysis in Streaming Call Graphs.- Scalable Cloud-Based Data Analysis Software Systems for Big Data From Next Generation Sequencing -- Discovering Networks of Interdependent Features in High-Dimensional Problems -- Final Remarks on Big Data Analysis and its Impact on Society and Science.
520 _aThis edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of Big Data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by Big Data Analysis are underlined, the book also discusses some of the warnings that have been issued concerning the potential dangers of Big Data Analysis along with its pitfalls and challenges.
650 0 _aComputational intelligence.
_97716
650 0 _aArtificial intelligence.
_93407
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aArtificial Intelligence.
_93407
700 1 _aJapkowicz, Nathalie.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_932643
700 1 _aStefanowski, Jerzy.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_932644
710 2 _aSpringerLink (Online service)
_932645
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319269870
776 0 8 _iPrinted edition:
_z9783319269887
776 0 8 _iPrinted edition:
_z9783319800530
830 0 _aStudies in Big Data,
_x2197-6511 ;
_v16
_932646
856 4 0 _uhttps://doi.org/10.1007/978-3-319-26989-4
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c75283
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