Big Data for the Greater Good
Editors: Emrouznejad, Ali, Charles, Vincent (Eds.)
Free Preview- Highlights recent developments and challenges in Big Data
- Introduces novel optimization algorithms and codes that can be used in the Big Data setting and are useful for the public
- Written by respected experts in the field
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- About this book
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This book highlights some of the most fascinating current uses, thought-provoking changes, and biggest challenges that Big Data means for our society. The explosive growth of data and advances in Big Data analytics have created a new frontier for innovation, competition, productivity, and well-being in almost every sector of our society, as well as a source of immense economic and societal value. From the derivation of customer feedback-based insights to fraud detection and preserving privacy; better medical treatments; agriculture and food management; and establishing low-voltage networks – many innovations for the greater good can stem from Big Data. Given the insights it provides, this book will be of interest to both researchers in the field of Big Data, and practitioners from various fields who intend to apply Big Data technologies to improve their strategic and operational decision-making processes.
- About the authors
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- Table of contents (9 chapters)
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Big Data for the Greater Good: An Introduction
Pages 1-18
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Big Data Analytics and Ethnography: Together for the Greater Good
Pages 19-33
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Big Data: A Global Overview
Pages 35-50
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Big Data for Predictive Analytics in High Acuity Health Settings
Pages 51-100
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A Novel Big Data-Enabled Approach, Individualizing and Optimizing Brain Disorder Rehabilitation
Pages 101-127
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Table of contents (9 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Big Data for the Greater Good
- Editors
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- Ali Emrouznejad
- Vincent Charles
- Series Title
- Studies in Big Data
- Series Volume
- 42
- Copyright
- 2019
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing AG, part of Springer Nature
- eBook ISBN
- 978-3-319-93061-9
- DOI
- 10.1007/978-3-319-93061-9
- Hardcover ISBN
- 978-3-319-93060-2
- Series ISSN
- 2197-6503
- Edition Number
- 1
- Number of Pages
- X, 204
- Number of Illustrations
- 21 b/w illustrations, 34 illustrations in colour
- Topics
