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Data intensive computing application...

Mittal, Mamta,

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Data intensive computing applications for big data

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data intensive computing applications for big data/ edited by Mamta Mittal, Valentina E. Balas, D. Jude Hemanth, and Raghvendra Kumar.
其他作者:	Mittal, Mamta,
出版者:	Amsterdam, Netherlands :IOS Press, : 2018.,
面頁冊數:	1 online resource (xvi, 601 p.)
附註:	Includes indexes.
內容註:	Title Page; About the Book; About the Editors; Preface; Contents; A Survey of Diversified Domain of Big Data Technologies; Big Data Technologies; Steps for Implementing Big Data and Its Security Challenges; Big Data Security Solutions in Cloud; Big Data Analysis in Cloud Using Machine Learning; Big Data Analysis Using Machine Learning Approach to Compute Data; Data Intensive Computing Application for Big Data; Uncertainty Detection in Unstructured Big Data; Parallel Computing: A Paradigm to Unimaginable Computing Speed and Efficiency
內容註:	Application of Big Data Analytics in Cloud Computing via Machine LearningA Novel Mechanism for Cloud Data Management in Distributed Environment; Spark SQL with Hive Context or SQL Context; Renewing Computing Paradigms for More Efficient Parallelization of Single-Threads; MongoDB as an Efficient Graph Database: An Application of Document Oriented NOSQL Database; Big Data Analytics for Prevention and Control of HIV/AIDS; Performance Analysis of Deadlock Prevention and MUTEX Detection Algorithms in Distributed Environment
內容註:	Real Time Location Tracking Map Matching Approaches for Road Navigation ApplicationsAccurate Prediction of Life Style Based Disorders by Smart Healthcare Using Machine Learning and Prescriptive Big Data Analytics; Parallel Computing Contrive Optimized NFB Through QEEG & LENS Approach; S-ARRAY: Highly Scalable Parallel Sorting Algorithm; Protein Synthesis Based Discretization Method for Knowledge Discovery; Scala Programming for Big-Data Application; Fading Channel and Imperfect Channel Estimation for OFDM in Wireless Communication
內容註:	Blockchain Innovation and Its Impact on Business Banking OperationsSubject Index; Author Index
標題:	Big data. -
電子資源:	http://ebooks.windeal.com.tw/ios/cover.asp?isbn=9781614998136
ISBN:	9781614998143 (e-book)

Data intensive computing applications for big data
Data intensive computing applications for big dataedited by Mamta Mittal, Valentina E. Balas, D. Jude Hemanth, and Raghvendra Kumar. - Amsterdam, Netherlands :IOS Press,2018. - 1 online resource (xvi, 601 p.) - Advances in parallel computing ;v. 29. - Advances in parallel computing ;v. 29..

Includes indexes.

Title Page; About the Book; About the Editors; Preface; Contents; A Survey of Diversified Domain of Big Data Technologies; Big Data Technologies; Steps for Implementing Big Data and Its Security Challenges; Big Data Security Solutions in Cloud; Big Data Analysis in Cloud Using Machine Learning; Big Data Analysis Using Machine Learning Approach to Compute Data; Data Intensive Computing Application for Big Data; Uncertainty Detection in Unstructured Big Data; Parallel Computing: A Paradigm to Unimaginable Computing Speed and Efficiency

ISBN: 9781614998143 (e-book)Subjects--Topical Terms:

2045508
Big data.

LC Class. No.: QA76.9.B45 / D37 2018

Dewey Class. No.: 005.7

Data intensive computing applications for big data
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505 8 $a Application of Big Data Analytics in Cloud Computing via Machine LearningA Novel Mechanism for Cloud Data Management in Distributed Environment; Spark SQL with Hive Context or SQL Context; Renewing Computing Paradigms for More Efficient Parallelization of Single-Threads; MongoDB as an Efficient Graph Database: An Application of Document Oriented NOSQL Database; Big Data Analytics for Prevention and Control of HIV/AIDS; Performance Analysis of Deadlock Prevention and MUTEX Detection Algorithms in Distributed Environment
505 8 $a Real Time Location Tracking Map Matching Approaches for Road Navigation ApplicationsAccurate Prediction of Life Style Based Disorders by Smart Healthcare Using Machine Learning and Prescriptive Big Data Analytics; Parallel Computing Contrive Optimized NFB Through QEEG & LENS Approach; S-ARRAY: Highly Scalable Parallel Sorting Algorithm; Protein Synthesis Based Discretization Method for Knowledge Discovery; Scala Programming for Big-Data Application; Fading Channel and Imperfect Channel Estimation for OFDM in Wireless Communication
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