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Techniques and environments for big data analysis [electronic resource] : parallel, cloud, and grid computing / Bhabani Shankar Prasad Mishra, Satchidananda Dehuri, Euiwhan Kim, Gi-Name Wang, editors.

Mishra, Bhabani Shankar Prasad, editor.; Dehuri, Satchidananda, editor.; Kim, Euiwhan, editor.; Wang, Gi-Name, editor.
2016
QA76.9.B45
Available Online
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Title
Techniques and environments for big data analysis [electronic resource] : parallel, cloud, and grid computing / Bhabani Shankar Prasad Mishra, Satchidananda Dehuri, Euiwhan Kim, Gi-Name Wang, editors.
ISBN
9783319275208 (electronic book)
3319275208 (electronic book)
9783319275185
DOI
https://doi.org/10.1007/978-3-319-27520-8
Published
[Cham] : Springer, 2016.
Language
English
Description
1 online resource.
Item Number
10.1007/978-3-319-27520-8 doi
Call Number
QA76.9.B45
Dewey Decimal Classification
005.7
005
Summary
This volume is aiming at a wide range of readers and researchers in the area of Big Data by presenting the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chapters providing a concise introduction to Big Data Analysis and recent Techniques and Environments for Big Data Analysis. It gives insight into how the expensive fitness evaluation of evolutionary learning can play a vital role in big data analysis by adopting Parallel, Grid, and Cloud computing environments.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (viewed February 12, 2016)
Added Author
Mishra, Bhabani Shankar Prasad, editor.
Dehuri, Satchidananda, editor.
Kim, Euiwhan, editor.
Wang, Gi-Name, editor.
Series
Studies in big data ; 17.
Available in Other Form
Print version: 9783319275185
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
Introduction to Big Data Analysis
Parallel Environments
A Deep Dive into the Hadoop World to Explore its Various Performances
Natural Language Processing and Machine Learning for Big Data
Big Data and Cyber Foraging: Future Scope and Challenges
Parallel GA in Big Data Analysis
Evolutionary Algorithm Based Techniques to Handle Big Data
Statistical and Evolutionary Feature Selection Techniques Parallelized using MapReduce Programming Model
A Data Aware Scheme for Scheduling Big-Data Applications on SAVANNA Hadoop
The Role of Grid Technologies: A Next Level Combat with Big Data.

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