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Titlebook: Big Data for the Greater Good; Ali Emrouznejad,Vincent Charles Book 2019 Springer International Publishing AG, part of Springer Nature 201

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發(fā)表于 2025-3-21 20:08:05 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Big Data for the Greater Good
影響因子2023Ali Emrouznejad,Vincent Charles
視頻videohttp://file.papertrans.cn/186/185693/185693.mp4
發(fā)行地址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
學科分類Studies in Big Data
圖書封面Titlebook: Big Data for the Greater Good;  Ali Emrouznejad,Vincent Charles Book 2019 Springer International Publishing AG, part of Springer Nature 201
影響因子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..
Pindex Book 2019
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https://doi.org/10.1007/b101190alance training and Scope—a system collecting physiological data, is provided both in collaborating rehabilitation centers and at patient homes. The preliminary results are documented using a case study confirming that the approach offers a viable way towards the greater good of a patient.
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https://doi.org/10.1007/978-3-031-53558-1 present confidence bounds that allow us to measure uncertainty of the uptake based on different scenarios. Finally, two case-studies are reported, describing applications of these techniques to energy modelling on a real low-voltage network in Bracknell, UK. These studies show how applying agent-ba
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Big Data for the Greater Good: An Introduction, of the social value that can be extracted from it; to this aim, we explore some of the key literature on the subject. We also call attention to the potential ‘dark’ side of Big Data, but argue that more studies are needed to fully understand the downside of it. We conclude this chapter with some fi
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Big Data and Sensitive Data,g trustee institutions and foster new types of data collaborations and business models. The chapter provides an introduction to CoED, and presents CoED applications for collaborative statistics when applied to financial risk assessment in banks and directly to the banks’ customers. Another applicati
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