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Techniques and Environments for Big Data Analysis

Parallel, Cloud, and Grid Computing

  • Book
  • © 2016

Overview

Editors:
  1. Bhabani Shankar Prasad Mishra

    1. School of Computer, KIIT University, Bhubaneswar, India

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  2. Satchidananda Dehuri

    1. Fakir Mohan University, Department of Information and Communicat, Odisha, India

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  3. Euiwhan Kim

    1. Department of Systems Engineering, Ajou University, Suwon, Korea (Republic of)

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  4. Gi-Name Wang

    1. Department of Industrial Engineerin, Ajou University, Suwon, Korea (Republic of)

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  • Presents the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it
  • Emphasis is on theoretical advances of Big Data and it’s practices in parallel, cloud, and grid environment
  • Interesting and novel collection useful for researchers and students
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Big Data (SBD, volume 17)

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. Introduction to Big Data Analysis

    • Kiranjit Pattnaik, Bhabani Shankar Prasad Mishra
    Pages 1-20

  3. Parallel Environments

    • Bhabani Shankar Prasad Mishra, Santwana Sagnika
    Pages 21-30

  4. A Deep Dive into the Hadoop World to Explore Its Various Performances

    • Dipayan Dev, Ripon Patgiri
    Pages 31-51

  5. Natural Language Processing and Machine Learning for Big Data

    • Joy Mustafi
    Pages 53-74

  6. Big Data and Cyber Foraging: Future Scope and Challenges

    • Chhabi Rani Panigrahi, Mayank Tiwary, Bibudhendu Pati, Himansu Das
    Pages 75-100

  7. Parallel GA in Big Data Analysis

    • Santwana Sagnika, Bhabani Shankar Prasad Mishra, Satchidananda Dehuri
    Pages 101-111

  8. Evolutionary Algorithm Based Techniques to Handle Big Data

    • Ghosh Sanchita, Desarkar Anindita
    Pages 113-158

  9. Statistical and Evolutionary Feature Selection Techniques Parallelized Using MapReduce Programming Model

    • M. Janaki Meena, S. P. Syed Ibrahim
    Pages 159-180

  10. The Role of Grid Technologies: A Next Level Combat with Big Data

    • Manoj Kumar Mishra, Yashwant Singh Patel
    Pages 181-191
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Keywords

About this book

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.

Editors and Affiliations

  • School of Computer, KIIT University, Bhubaneswar, India

    Bhabani Shankar Prasad Mishra

  • Fakir Mohan University, Department of Information and Communicat, Odisha, India

    Satchidananda Dehuri

  • Department of Systems Engineering, Ajou University, Suwon, Korea (Republic of)

    Euiwhan Kim

  • Department of Industrial Engineerin, Ajou University, Suwon, Korea (Republic of)

    Gi-Name Wang

Bibliographic Information

  • Book Title: Techniques and Environments for Big Data Analysis

  • Book Subtitle: Parallel, Cloud, and Grid Computing

  • Editors: Bhabani Shankar Prasad Mishra, Satchidananda Dehuri, Euiwhan Kim, Gi-Name Wang

  • Series Title: Studies in Big Data

  • DOI: https://doi.org/10.1007/978-3-319-27520-8

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing Switzerland 2016

  • Hardcover ISBN: 978-3-319-27518-5Published: 16 February 2016

  • Softcover ISBN: 978-3-319-80160-5Published: 30 March 2018

  • eBook ISBN: 978-3-319-27520-8Published: 05 February 2016

  • Series ISSN: 2197-6503

  • Series E-ISSN: 2197-6511

  • Edition Number: 1

  • Number of Pages: XI, 191

  • Number of Illustrations: 27 b/w illustrations, 76 illustrations in colour

  • Topics: Computational Intelligence, Data Mining and Knowledge Discovery, Artificial Intelligence

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