1.

Record Nr.

UNINA9910739427803321

Titolo

Techniques and Environments for Big Data Analysis : Parallel, Cloud, and Grid Computing / / edited by B. S.P. Mishra, Satchidananda Dehuri, Euiwhan Kim, Gi-Name Wang

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016

ISBN

9783319275208

3319275208

Edizione

[1st ed. 2016.]

Descrizione fisica

1 online resource (199 p.)

Collana

Studies in Big Data, , 2197-6503 ; ; 17

Classificazione

32.24

Disciplina

005.74023

Soggetti

Computational intelligence

Data mining

Artificial intelligence

Computational Intelligence

Data Mining and Knowledge Discovery

Artificial Intelligence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references at the end of each chapters.

Nota di contenuto

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.

Sommario/riassunto

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.