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.