Big Data Analysis: New Algorithms for a New Society - Studies in Big Data
Big Data Analysis: New Algorithms for a New Society - Studies in Big Data
hardback
Published:
28 December, 2015
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Description
This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area.
It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of Big Data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by Big Data Analysis are underlined, the book also discusses some of the warnings that have been issued concerning the potential dangers of Big Data Analysis along with its pitfalls and challenges.
More Details
| Type | Book |
|---|---|
| ISBN13 | 9783319269870 |
| ISBN10 | 3319269879 |
| Number Of Pages | 329 |
| Item Weight | 1000 g |
| Publisher / Reseller | Springer International Publishing AG |
| Format | hardback |
| Edition | 1st ed. 2016 |
Media Reviews
“This book can be used as a reference book on big data analysis with a tilt toward machine learning techniques. Individual chapters could be useful to interested parties in the respective areas of research. Big data analytics is a relatively new problem in the domain of civilian activities, although it has a longer history in military applications. This edited volume certainly fills a niche in this growing and broad research area.” (M. M. Tanik, Computing Reviews, computingreviews.com, June, 2016)