Business Information Systems (eBook, PDF)
22nd International Conference, BIS 2019, Seville, Spain, June 26-28, 2019, Proceedings, Part I
Redaktion: Abramowicz, Witold; Corchuelo, Rafael
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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; Art...
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.
The chapter "Time Series Forecasting by Recommendation: An Empirical Analysis on Amazon Marketplace" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
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.
The chapter "Time Series Forecasting by Recommendation: An Empirical Analysis on Amazon Marketplace" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
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