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Techniques and Environments for Big Data Analysis : Parallel, Cloud, and Grid Computing / edited by Bhabani Shankar Prasad Mishra, Satchidananda Dehuri, Euiwhan Kim, Gi-Name Wang

Contributor(s): SpringerLink (Online service) | Mishra, Bhabani Shankar Prasad., editor literario | Dehuri, Satchidananda, editor literario | Kim, Euiwhan, editor literario | Wang, Gi-Name., editor literario
Material type: materialTypeLabelE-bookSeries: (Studies in Big Data, 2197-6503; 17).Publisher: Cham : Springer International Publishing, 2016Edition: 1st ed.Description: 1 recurso en línea (XI, 191 páginas) : 103 ilustraciones, 27 ilustraciones en color.ISBN: 9783319275208.Subject: Inteligencia artificial | Estructuras de datos (Informática)DDC classification: 006.3 Online resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
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.
Abstract: 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.
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Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería QA76.9.B45 T434 2016 EB (Browse shelf(Opens below)) .i11589978 Acceso electrónico eBOOK .i11589978
Total holds: 0

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.

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.

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