Techniques and Environments for Big Data Analysis: Parallel, Cloud, and Grid Computing
Techniques and Environments for Big Data Analysis: Parallel, Cloud, and Grid Computing
Springer | Studies in Big Data | March 8, 2016 | ISBN-10: 3319275186 | 191 pages | pdf | 7.29 mb
Springer | Studies in Big Data | March 8, 2016 | ISBN-10: 3319275186 | 191 pages | pdf | 7.29 mb
Editors: Mishra, B.S.P., Dehuri, S., Kim, E., Wang, G.-N. (Eds.)
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
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.
Number of Illustrations and Tables
76 b/w illustrations, 27 illustrations in colour
Topics
Computational Intelligence
Data Mining and Knowledge Discovery
Artificial Intelligence (incl. Robotics)
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