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Titlebook: Big Data Analytics; Methods and Applicat Saumyadipta Pyne,B.L.S. Prakasa Rao,S.B. Rao Book 2016 Springer India 2016 Big Data.Computational

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期刊全称Big Data Analytics
期刊简称Methods and Applicat
影响因子2023Saumyadipta Pyne,B.L.S. Prakasa Rao,S.B. Rao
视频video
发行地址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
图书封面Titlebook: Big Data Analytics; Methods and Applicat Saumyadipta Pyne,B.L.S. Prakasa Rao,S.B. Rao Book 2016 Springer India 2016 Big Data.Computational
影响因子.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..
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Application of Mixture Models to Large Datasets,sider normal and .-mixture models. As they are highly parameterized, we review methods to enable them to be fitted to large datasets involving many observations and variables. Attention is then given to extensions of these mixture models to mixtures with skew normal and skew .-distributions for the
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Application-Level Benchmarking of Big Data Systems, phenomenon. The amount, rate, and variety of data that are assembled—for almost any application domain—are necessitating a reexamination of old technologies and development of new technologies to get value from the data, in a timely fashion. With increasing adoption and penetration of mobile techno
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