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020 _a9783030034931
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024 7 _a10.1007/978-3-030-03493-1
_2doi
050 4 _aQA76.9.D343
072 7 _aUNF
_2bicssc
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072 7 _aUNF
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072 7 _aUYQE
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082 0 4 _a006.312
_223
245 1 0 _aIntelligent Data Engineering and Automated Learning - IDEAL 2018
_h[electronic resource] :
_b19th International Conference, Madrid, Spain, November 21-23, 2018, Proceedings, Part I /
_cedited by Hujun Yin, David Camacho, Paulo Novais, Antonio J. Tallón-Ballesteros.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXXVI, 865 p. 285 illus., 197 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 _aInformation Systems and Applications, incl. Internet/Web, and HCI,
_x2946-1642 ;
_v11314
505 0 _aIntelligent data analysis -- data mining and their associated learning systems and paradigms -- big data challenges -- machine learning, data mining, information retrieval and management -- bio- and neuro-informatics -- bio-inspired models including neural networks, evolutionary computation and swarm intelligence -- agents and hybrid intelligent systems, and real-world applications of intelligent techniques -- evolutionary algorithms -- deep learning neural networks -- probabilistic modeling -- particle swarm intelligence -- big data analytics and applications in image recognition -- regression, classification, clustering, medical and biological modelling and prediction -- text processing and social media analysis.
520 _aThis two-volume set LNCS 11314 and 11315 constitutes the thoroughly refereed conference proceedings of the 19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018, held in Madrid, Spain, in November 2018. The 125 full papers presented were carefully reviewed and selected from 204 submissions. These papers provided a timely sample of the latest advances in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, deep learning neural networks, probabilistic modelling, particle swarm intelligence, big data analytics, and applications in image recognition, regression, classification, clustering, medical and biological modelling and prediction, text processing and social media analysis.
650 0 _aData mining.
_93907
650 0 _aArtificial intelligence.
_93407
650 0 _aImage processing
_xDigital techniques.
_94145
650 0 _aComputer vision.
_9108378
650 0 _aComputer science.
_99832
650 1 4 _aData Mining and Knowledge Discovery.
_9108379
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_931569
650 2 4 _aTheory of Computation.
_9108380
700 1 _aYin, Hujun.
_eeditor.
_0(orcid)
_10000-0002-9198-5401
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9108381
700 1 _aCamacho, David.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9108382
700 1 _aNovais, Paulo.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9108383
700 1 _aTallón-Ballesteros, Antonio J.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9108384
710 2 _aSpringerLink (Online service)
_9108385
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030034924
776 0 8 _iPrinted edition:
_z9783030034948
830 0 _aInformation Systems and Applications, incl. Internet/Web, and HCI,
_x2946-1642 ;
_v11314
_9108386
856 4 0 _uhttps://doi.org/10.1007/978-3-030-03493-1
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