Editors:
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11708)
Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)
Conference series link(s): DaWaK: International Conference on Big Data Analytics and Knowledge Discovery
Conference proceedings info: DaWaK 2019.
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Table of contents (22 papers)
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Front Matter
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Patterns
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Front Matter
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About this book
This book constitutes the refereed proceedings of the 21st International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2019, held in Linz, Austria, in September 2019.
The 12 full papers and 10 short papers presented were carefully reviewed and selected from 61 submissions. The papers are organized in the following topical sections: Applications; patterns; RDF and streams; big data systems; graphs and machine learning; databases.
Editors and Affiliations
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University of Houston, Houston, USA
Carlos Ordonez
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Drexel University, Philadelphia, USA
Il-Yeol Song
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Johannes Kepler University of Linz, Linz, Austria
Gabriele Anderst-Kotsis, Ismail Khalil
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Software Competence Center Hagenberg, Hagenberg im Mühlkreis, Austria
A Min Tjoa
Bibliographic Information
Book Title: Big Data Analytics and Knowledge Discovery
Book Subtitle: 21st International Conference, DaWaK 2019, Linz, Austria, August 26–29, 2019, Proceedings
Editors: Carlos Ordonez, Il-Yeol Song, Gabriele Anderst-Kotsis, A Min Tjoa, Ismail Khalil
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-27520-4
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Softcover ISBN: 978-3-030-27519-8Published: 03 August 2019
eBook ISBN: 978-3-030-27520-4Published: 19 August 2019
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XIII, 321
Number of Illustrations: 84 b/w illustrations, 80 illustrations in colour
Topics: Database Management, Data Mining and Knowledge Discovery, Arithmetic and Logic Structures, System Performance and Evaluation, Artificial Intelligence