Big Data Analytics: Methods and Applications

✍ Scribed by Saumyadipta Pyne, B.L.S. Prakasa Rao, S.B. Rao (eds.)

Publisher: Springer India
Year: 2016
Tongue: English
Leaves: 278
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xii
Big Data Analytics: Views from Statistical and Computational Perspectives....Pages 1-10
Massive Data Analysis: Tasks, Tools, Applications, and Challenges....Pages 11-40
Statistical Challenges with Big Data in Management Science....Pages 41-55
Application of Mixture Models to Large Datasets....Pages 57-74
An Efficient Partition-Repetition Approach in Clustering of Big Data....Pages 75-93
Online Graph Partitioning with an Affine Message Combining Cost Function....Pages 95-114
Big Data Analytics Platforms for Real-Time Applications in IoT....Pages 115-135
Complex Event Processing in Big Data Systems....Pages 137-161
Unwanted Traffic Identification in Large-Scale University Networks: A Case Study....Pages 163-187
Application-Level Benchmarking of Big Data Systems....Pages 189-199
Managing Large-Scale Standardized Electronic Health Records....Pages 201-219
Microbiome Data Mining for Microbial Interactions and Relationships....Pages 221-235
A Nonlinear Technique for Analysis of Big Data in Neuroscience....Pages 237-257
Big Data and Cancer Research....Pages 259-276

✦ Subjects

Statistics and Computing/Statistics Programs;Statistics for Life Sciences, Medicine, Health Sciences;Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law;Statistics for Business/Economics/Mathematical Fin

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