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E-book
Author International Conference on Data Analytics and Management in Data Intensive Domains (22nd : 2020 : Online)

Title Data analytics and management in data intensive domains : 22nd International Conference, DAMDID/RCDL 2020, Voronezh, Russia, October 13-16, 2020, selected proceedings / Alexander Sychev, Sergey Makhortov, Bernhard Thalheim (eds.)
Published Cham : Springer, [2021]
©2021

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Description 1 online resource : illustrations (some color)
Series Communications in computer and information science, 1865-0929 ; 1427
Communications in computer and information science ; 1427. 1865-0929
Contents Keynote Abstracts -- Data Integration, Conceptual Models and Ontologies -- Data Management in Semantic Web -- Data Analysis in Medicine -- Data Analysis in Astronomy -- Information Extraction from Text
Summary This book constitutes the post-conference proceedings of the 22nd International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2020, held in Voronezh, Russia, in October 2020*. The 16 revised full papers and two keynotes were carefully reviewed and selected from 60 submissions. The papers are organized in the following topical sections: data Integration, conceptual models and ontologies; data management in semantic web; data analysis in medicine; data analysis in astronomy; information extraction from text. * The conference was held virtually due to the COVID-19 pandemic
Notes International conference proceedings
Includes index
Online resource; title from PDF title page (SpringerLink, viewed July 28, 2021)
Subject Management information systems -- Congresses
Knowledge management -- Congresses
Information technology -- Congresses
Information technology
Knowledge management
Management information systems
Genre/Form proceedings (reports)
Conference papers and proceedings
Conference papers and proceedings.
Actes de congrès.
Form Electronic book
Author Sychev, Alexander, editor
Makhortov, Sergey, editor
Thalheim, Bernhard, editor
ISBN 9783030812003
3030812006
Other Titles DAMDID/RCDL 2020