Big Data Analytics
Methods and Applications

Editors: Saumyadipta Pyne, B.L.S. Prakasa Rao, S.B. Rao



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

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

Big Data Analytics: Views from Statistical and Computational Perspectives

Massive Data Analysis: Tasks, Tools, Applications, and Challenges

Statistical Challenges with Big Data in Management Science

Application of Mixture Models to Large Datasets

An Efficient Partition-Repetition Approach in Clustering of Big Data

Online Graph Partitioning with an Affine Message Combining Cost Function

Big Data Analytics Platforms for Real-Time Applications in IoT

Complex Event Processing in Big Data Systems

Unwanted Traffic Identification in Large-Scale University Networks: A Case Study

Application-Level Benchmarking of Big Data Systems

Managing Large-Scale Standardized Electronic Health Records

Microbiome Data Mining for Microbial Interactions and Relationships

A Nonlinear Technique for Analysis of Big Data in Neuroscience

Big Data and Cancer Research

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