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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
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072 7 _aUNF
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082 0 4 _a006.312
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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.
650 0 _aArtificial intelligence.
650 0 _aImage processing
_xDigital techniques.
650 0 _aComputer vision.
650 0 _aComputer science.
650 1 4 _aData Mining and Knowledge Discovery.
650 2 4 _aArtificial Intelligence.
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
650 2 4 _aTheory of Computation.
700 1 _aYin, Hujun.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aCamacho, David.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aNovais, Paulo.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aTallón-Ballesteros, Antonio J.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
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
856 4 0 _uhttps://doi.org/10.1007/978-3-030-03493-1
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
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