Discovery science : 22nd International Conference, DS 2019, Split, Croatia, October 28-30, 2019, Proceedings /

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Bibliographic Details
Meeting name:	International Conference on Discovery Science (22nd : 2019 : Split, Croatia)
Imprint:	Cham, Switzerland : Springer, 2019.
Description:	1 online resource (xxii, 546 pages) : illustrations (some color).
Language:	English
Series:	Lecture Notes in Artificial Intelligence Lecture notes in computer science ; 11828 LNCS sublibrary. SL 7, Artificial intelligence Lecture notes in computer science. Lecture notes in artificial intelligence. Lecture notes in computer science ; 11828. LNCS sublibrary. SL 7, Artificial intelligence.
Subject:	Science -- Philosophy -- Congresses. Discoveries in science -- Congresses. Research -- Automation -- Congresses. Machine learning -- Congresses. Data mining -- Congresses. Data mining. Discoveries in science. Machine learning. Research -- Automation. Science -- Philosophy. Conference papers and proceedings.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11981683

Hidden Bibliographic Details
Varying Form of Title:	DS 2019
Other authors / contributors:	Kralj Novak, Petra, editor. Šmuc, Tomislav, editor. Džeroski, Sašo, 1968- editor.
ISBN:	9783030337780 3030337782 9783030337773
Notes:	International conference proceedings. Incldues author index. Online resource; title from PDF title page (SpringerLink, viewed October 23, 2019).
Summary:	This book constitutes the proceedings of the 22nd International Conference on Discovery Science, DS 2019, held in Split, Coratia, in October 2019. The 21 full and 19 short papers presented together with 3 abstracts of invited talks in this volume were carefully reviewed and selected from 63 submissions. The scope of the conference includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, big data analysis as well as their application in various scientific domains. The papers are organized in the following topical sections: Advanced Machine Learning; Applications; Data and Knowledge Representation; Feature Importance; Interpretable Machine Learning; Networks; Pattern Discovery; and Time Series.
Standard no.:	10.1007/978-3-030-33778-0 10.1007/978-3-030-33

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