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020			_a9789811685316
024	7		_a10.1007/978-981-16-8531-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9 .D343 _b2021 EB
245	1	0	_aData Mining : _b19th Australasian Conference on Data Mining, AusDM 2021, Brisbane, QLD, Australia, December 14-15, 2021, Proceedings _cedited by Yue Xu, Rosalind Wang, Anton Lord, Yee Ling Boo, Richi Nayak, Yanchang Zhao, Graham Williams
250			_aFirst edition 2021
264		1	_aSingapore _bSpringer International Publising _c2021
300			_a1 recurso en línea (XII, 235 páginas) _b61 ilustraciones, 45 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aCommunications in Computer and Information Science _x1865-0937 _v1504
490	0		_aComputer Science (SpringerNature-11645)
490	0		_aComputer Science (R0) (SpringerNature-43710)
505	0		_aResearch Track -- Parallel Nonlinear Dimensionality Reduction Using GPU Acceleration -- Taking the Confusion out of Multinomial Confusion Matrices and Imbalanced Classes -- Sharpshooting Most Beneficial Part of AUC for Detecting Malicious Logs -- A Drift Aware Hierarchical Test based Approach for Combating Spammers in Online Social Networks -- Hospital Readmission Prediction Using Semantic Relations Between Medical Codes -- HFM++: An Enhanced Holographic Factorization Machine for Recommendation -- Deep Learning for Bias Detection: From Inception to Deployment -- Exploring Fusion Strategies in Deep Learning Models for Multi-modal Classification -- Application Track -- Chameleon: A Python Workflow Toolkit for Feature Selection -- PostMatch: A Framework for Efficient Address Matching -- Detection of Classical Cipher Types with Feature-Learning Approach -- SOMPS-Net: Attention based Social Graph Framework for Early Detection of Fake Health News -- How to Read the News: A Study of How Sentiment Effects Financial Markets -- Investigation of Topic Modelling Methods for Understanding the Reports of the Mining Projects in Queensland -- A Semi-Automatic Data Extraction System for Heterogeneous Data Sources: A Case Study from Cotton Industry -- Nonnegative Matrix Factorization to Understand Spatio-Temporal Traffic Pattern Variations during COVID-19: A Case Study.
520	3		_aThis book constitutes the refereed proceedings of the 19th Australasian Conference on Data Mining, AusDM 2021, held in Brisbane, Queensland, Australia, in December 2021.* The 16 revised full papers presented were carefully reviewed and selected from 32 submissions. The papers are organized in sections on research track and application track. *Due to the COVID-19 pandemic the conference was held online. .
988			_aSpringer_Computer_2021
650		7	_2embne _9162648 _aData mining _vCongresos y asambleas
700	1		_aXu, Yue _eeditor literario _0(orcid)0000-0002-1137-0272 _1https://orcid.org/0000-0002-1137-0272 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aWang, Rosalind _eeditor literario _0(orcid)0000-0001-5454-6197 _1https://orcid.org/0000-0001-5454-6197 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aLord, Anton _eeditor literario _0(orcid)0000-0003-2405-9827 _1https://orcid.org/0000-0003-2405-9827 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aBoo, Yee Ling _eeditor literario _0(orcid)0000-0001-7188-9597 _1https://orcid.org/0000-0001-7188-9597 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aNayak, Richi _eeditor literario _0(orcid)0000-0002-9954-0159 _1https://orcid.org/0000-0002-9954-0159 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aZhao, Yanchang _eeditor literario _0(orcid)0000-0002-0209-3971 _1https://orcid.org/0000-0002-0209-3971 _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aWilliams, Graham _eeditor literario _0(orcid)0000-0001-7041-4127 _1https://orcid.org/0000-0001-7041-4127 _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition _z9789811685309
776	0	8	_iPrinted edition _z9789811685323
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-16-8531-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2022 _dz _eh _zSI