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Big Data for the Greater Good
~
Emrouznejad, Ali.
Big Data for the Greater Good
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Big Data for the Greater Good/ edited by Ali Emrouznejad, Vincent Charles.
other author:
Emrouznejad, Ali.
Description:
X, 204 p. 55 illus., 34 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Computational intelligence. -
Online resource:
https://doi.org/10.1007/978-3-319-93061-9
ISBN:
9783319930619
Big Data for the Greater Good
Big Data for the Greater Good
[electronic resource] /edited by Ali Emrouznejad, Vincent Charles. - 1st ed. 2019. - X, 204 p. 55 illus., 34 illus. in color.online resource. - Studies in Big Data,422197-6503 ;. - Studies in Big Data,8.
Big Data for the Greater Good: An Introduction -- Big Data Analytics and Ethnography: Together for the Greater Good -- Big Data: A Global Overview -- Big data for predictive analytics in high acuity health settings -- A Novel Big Data-Enabled Approach Individualizing and Optimizing Brain Disorder Rehabilitation -- Big Data in Agricultural and Food Research: Challenges and Opportunities of an integrated Big Data e-Infrastructure -- Green neighbourhoods: the role of big data in low voltage networks' planning -- Big Data Improves Visitor Experience at Local, State, and National Parks – Natural Language Processing Applied to Customer Feedback -- Big Data and Sensitive Data.
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.
ISBN: 9783319930619
Standard No.: 10.1007/978-3-319-93061-9doiSubjects--Topical Terms:
568984
Computational intelligence.
LC Class. No.: Q342
Dewey Class. No.: 006.3
Big Data for the Greater Good
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Big Data for the Greater Good: An Introduction -- Big Data Analytics and Ethnography: Together for the Greater Good -- Big Data: A Global Overview -- Big data for predictive analytics in high acuity health settings -- A Novel Big Data-Enabled Approach Individualizing and Optimizing Brain Disorder Rehabilitation -- Big Data in Agricultural and Food Research: Challenges and Opportunities of an integrated Big Data e-Infrastructure -- Green neighbourhoods: the role of big data in low voltage networks' planning -- Big Data Improves Visitor Experience at Local, State, and National Parks – Natural Language Processing Applied to Customer Feedback -- Big Data and Sensitive Data.
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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.
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