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Big Data Analytics

Overview of attention for book
Cover of 'Big Data Analytics'

Table of Contents

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    Book Overview
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    Chapter 1 Big Data Analytics: Views from Statistical and Computational Perspectives
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    Chapter 2 Massive Data Analysis: Tasks, Tools, Applications, and Challenges
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    Chapter 3 Statistical Challenges with Big Data in Management Science
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    Chapter 4 Application of Mixture Models to Large Datasets
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    Chapter 5 An Efficient Partition-Repetition Approach in Clustering of Big Data
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    Chapter 6 Online Graph Partitioning with an Affine Message Combining Cost Function
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    Chapter 7 Big Data Analytics Platforms for Real-Time Applications in IoT
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    Chapter 8 Complex Event Processing in Big Data Systems
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    Chapter 9 Unwanted Traffic Identification in Large-Scale University Networks: A Case Study
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    Chapter 10 Application-Level Benchmarking of Big Data Systems
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    Chapter 11 Managing Large-Scale Standardized Electronic Health Records
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    Chapter 12 Microbiome Data Mining for Microbial Interactions and Relationships
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    Chapter 13 A Nonlinear Technique for Analysis of Big Data in Neuroscience
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    Chapter 14 Big Data and Cancer Research
Attention for Chapter 4: Application of Mixture Models to Large Datasets
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Citations

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Chapter title
Application of Mixture Models to Large Datasets
Chapter number 4
Book title
Big Data Analytics
Published by
Springer India, October 2016
DOI 10.1007/978-81-322-3628-3_4
Book ISBNs
978-8-13-223626-9, 978-8-13-223628-3
Authors

Sharon X. Lee, Geoffrey McLachlan, Saumyadipta Pyne

Editors

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

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 1 50%
Student > Bachelor 1 50%
Readers by discipline Count As %
Business, Management and Accounting 1 50%
Computer Science 1 50%

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