Overview
Part of the book series: Lecture Notes in Business Information Processing (LNBIP, volume 353)
Included in the following conference series:
Conference proceedings info: BIS 2019.
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About this book
The two-volume set LNBIP 353 and 354 constitutes the proceedings of the 22nd International Conference on Business Information Systems, BIS 2019, held in Seville, Spain, in June 2019.
The theme of the BIS 2019 was "Data Science for Business Information Systems", inspiring researchers to share theoretical and practical knowledge of the different aspects related to Data Science in enterprises. The 67 papers presented in these proceedings were carefully reviewed and selected from 223 submissions.
The contributions were organized in topical sections as follows:
Part I: Big Data and Data Science; Artificial Intelligence; ICT Project Management; and Smart Infrastructure.
Part II: Social Media and Web-based Systems; and Applications, Evaluations and Experiences.
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Keywords
Table of contents (42 papers)
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Front Matter
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Big Data and Data Science
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Front Matter
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Artificial Intelligence
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Front Matter
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Other volumes
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Business Information Systems
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Business Information Systems
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Business Information Systems Workshops
Editors and Affiliations
Bibliographic Information
Book Title: Business Information Systems
Book Subtitle: 22nd International Conference, BIS 2019, Seville, Spain, June 26–28, 2019, Proceedings, Part I
Editors: Witold Abramowicz, Rafael Corchuelo
Series Title: Lecture Notes in Business Information Processing
DOI: https://doi.org/10.1007/978-3-030-20485-3
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Softcover ISBN: 978-3-030-20484-6Published: 18 May 2019
eBook ISBN: 978-3-030-20485-3Published: 18 June 2019
Series ISSN: 1865-1348
Series E-ISSN: 1865-1356
Edition Number: 1
Number of Pages: XVII, 541
Number of Illustrations: 155 b/w illustrations, 116 illustrations in colour
Topics: Information Systems Applications (incl. Internet), Business Information Systems, Data Mining and Knowledge Discovery, Big Data/Analytics, Enterprise Architecture, Software Engineering