Techniques and Environments for Big Data Analysis (Record no. 57383)
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fixed length control field | 03093nam a22005415i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-319-27520-8 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20200421112221.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 160205s2016 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783319275208 |
-- | 978-3-319-27520-8 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 006.3 |
245 10 - TITLE STATEMENT | |
Title | Techniques and Environments for Big Data Analysis |
Sub Title | Parallel, Cloud, and Grid Computing / |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2016. |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | XI, 191 p. 103 illus., 27 illus. in color. |
490 1# - SERIES STATEMENT | |
Series statement | Studies in Big Data, |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | 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. |
520 ## - SUMMARY, ETC. | |
Summary, etc | 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. |
700 1# - AUTHOR 2 | |
Author 2 | Mishra, Bhabani Shankar Prasad. |
700 1# - AUTHOR 2 | |
Author 2 | Dehuri, Satchidananda. |
700 1# - AUTHOR 2 | |
Author 2 | Kim, Euiwhan. |
700 1# - AUTHOR 2 | |
Author 2 | Wang, Gi-Name. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-319-27520-8 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks |
264 #1 - | |
-- | Cham : |
-- | Springer International Publishing : |
-- | Imprint: Springer, |
-- | 2016. |
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-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
338 ## - | |
-- | online resource |
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-- | rdacarrier |
347 ## - | |
-- | text file |
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-- | rda |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Engineering. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Data mining. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computational intelligence. |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Engineering. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computational Intelligence. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Data Mining and Knowledge Discovery. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial Intelligence (incl. Robotics). |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
-- | 2197-6503 ; |
912 ## - | |
-- | ZDB-2-ENG |
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