Big Data Analytics
Methods and Applications
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Beschreibung
This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.
This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.
Introduces new computational methods and key applications due to known international researchers and labs Provides different application areas in Big Data applications such as management, Internet of Things, genomics and healthcare Discusses some of the latest efforts in data standards and bench-marking of systems for Big Data Includes supplementary material: sn.pub/extras
Autor*in
Saumyadipta Pyne
Themen in »Big Data Analytics«
Big Data Computational Statistics Data Mining High-dimensional Data Data Science
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“The editors of this volume have assembled 13 papers by big data experts who participated in that conference, covering analytics and algorithms, benchmarks, use cases, problem statements, and solutions. … The book could serve as supplemental recommended reading for graduate data analytics courses … .” (Harry J. Foxwell, Computing Reviews, April, 2017)
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