Verfügbarkeit: Machine learning and knowledge discovery in databases

Machine learning and knowledge discovery in databases: European conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, proceedings, part VI

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Bibliographische Detailangaben
Körperschaft:	European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases Grenoble (VerfasserIn)
Weitere beteiligte Personen:	Amini, Massih-Reza (HerausgeberIn), Canu, Stéphane (HerausgeberIn), Fischer, Asja (HerausgeberIn), Guns, Tias (HerausgeberIn), Kralj Novak, Petra (HerausgeberIn), Tsoumakas, Grigorios (HerausgeberIn)
Format:	Elektronisch Tagungsbericht E-Book
Sprache:	Englisch
Veröffentlicht:	Cham, Switzerland Springer [2023]
Schriftenreihe:	Lecture notes in computer science 13718
Schlagwörter:	Artificial Intelligence Computing Milieux Computer Engineering and Networks Computer Imaging, Vision, Pattern Recognition and Graphics Software Engineering Computer Application in Social and Behavioral Sciences Artificial intelligence Computers Computer engineering Computer networks Image processing—Digital techniques Computer vision Software engineering Social sciences—Data processing Konferenzschrift > 2022 > Grenoble
Links:	https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1 https://doi.org/10.1007/978-3-031-26422-1
Umfang:	1 Online-Ressource (xlvii, 669 Seiten) 205 Illustrationen, 191 in Farbe
ISBN:	9783031264221
ISSN:	2945-9141
DOI:	10.1007/978-3-031-26422-1

Internformat

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genre	(DE-588)1071861417 Konferenzschrift 2022 Grenoble gnd-content
genre_facet	Konferenzschrift 2022 Grenoble
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indexdate	2025-03-04T05:00:13Z
institution	BVB
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language	English
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physical	1 Online-Ressource (xlvii, 669 Seiten) 205 Illustrationen, 191 in Farbe
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publishDate	2023
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publisher	Springer
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series	Lecture notes in computer science
series2	Lecture notes in computer science Lecture notes in artificial intelligence
spellingShingle	Machine learning and knowledge discovery in databases European conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, proceedings, part VI Lecture notes in computer science Artificial Intelligence Computing Milieux Computer Engineering and Networks Computer Imaging, Vision, Pattern Recognition and Graphics Software Engineering Computer Application in Social and Behavioral Sciences Artificial intelligence Computers Computer engineering Computer networks Image processing—Digital techniques Computer vision Software engineering Social sciences—Data processing
subject_GND	(DE-588)1071861417
title	Machine learning and knowledge discovery in databases European conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, proceedings, part VI
title_auth	Machine learning and knowledge discovery in databases European conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, proceedings, part VI
title_exact_search	Machine learning and knowledge discovery in databases European conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, proceedings, part VI
title_full	Machine learning and knowledge discovery in databases European conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, proceedings, part VI Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas, editors
title_fullStr	Machine learning and knowledge discovery in databases European conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, proceedings, part VI Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas, editors
title_full_unstemmed	Machine learning and knowledge discovery in databases European conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, proceedings, part VI Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas, editors
title_short	Machine learning and knowledge discovery in databases
title_sort	machine learning and knowledge discovery in databases european conference ecml pkdd 2022 grenoble france september 19 23 2022 proceedings part vi
title_sub	European conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, proceedings, part VI
topic	Artificial Intelligence Computing Milieux Computer Engineering and Networks Computer Imaging, Vision, Pattern Recognition and Graphics Software Engineering Computer Application in Social and Behavioral Sciences Artificial intelligence Computers Computer engineering Computer networks Image processing—Digital techniques Computer vision Software engineering Social sciences—Data processing
topic_facet	Artificial Intelligence Computing Milieux Computer Engineering and Networks Computer Imaging, Vision, Pattern Recognition and Graphics Software Engineering Computer Application in Social and Behavioral Sciences Artificial intelligence Computers Computer engineering Computer networks Image processing—Digital techniques Computer vision Software engineering Social sciences—Data processing Konferenzschrift 2022 Grenoble
url	https://doi.org/10.1007/978-3-031-26422-1
volume_link	(DE-604)BV014880109
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