Data intensive computing applications for big data /:
Gespeichert in:
| Weitere Verfasser: | , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam, Netherlands :
IOS Press,
2018.
|
| Schriftenreihe: | Advances in parallel computing ;
v. 29. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | 1 online resource (xvi, 601 pages) : illustrations |
| Bibliographie: | Includes bibliographical references and indexes. |
| ISBN: | 9781614998143 1614998140 |
Internformat
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| 505 | 0 | |a 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. | |
| 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. | |
| 505 | 8 | |a Blockchain Innovation and Its Impact on Business Banking OperationsSubject Index; Author Index. | |
| 650 | 0 | |a Big data. |0 http://id.loc.gov/authorities/subjects/sh2012003227 | |
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| contents | 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. 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. 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. Blockchain Innovation and Its Impact on Business Banking OperationsSubject Index; Author Index. |
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| illustrated | Illustrated |
| indexdate | 2024-11-27T13:28:18Z |
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| series | Advances in parallel computing ; |
| series2 | Advances in parallel computing ; |
| spelling | Data intensive computing applications for big data / edited by Mamta Mittal, Valentina E. Balas, D. Jude Hemanth, and Raghvendra Kumar. Amsterdam, Netherlands : IOS Press, 2018. 1 online resource (xvi, 601 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Advances in parallel computing ; volume 29 Online resource; title from PDF title page (EBSCO, viewed April 23, 2018). Includes bibliographical references and 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. 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. 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. Blockchain Innovation and Its Impact on Business Banking OperationsSubject Index; Author Index. Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Données volumineuses. COMPUTERS Databases Data Warehousing. bisacsh Big data fast Mittal, Mamta, editor. https://id.oclc.org/worldcat/entity/E39PCjxvqCYCpqMBjwRvRYtvQC http://id.loc.gov/authorities/names/n96900490 Balas, Valentina Emilia, editor. https://id.oclc.org/worldcat/entity/E39PBJjCPfdqQJyMpDymx8gdwC http://id.loc.gov/authorities/names/no2009108627 Hemanth, D. Jude, editor. https://id.oclc.org/worldcat/entity/E39PCjCtKtPYBFBrrhpkqkMWwC http://id.loc.gov/authorities/names/no2018072240 Kumar, Raghvendra, 1987- editor. https://id.oclc.org/worldcat/entity/E39PCjMkXk4d6j4gPxfXFDryVC has work: Data intensive computing applications for big data (Text) https://id.oclc.org/worldcat/entity/E39PCH3b6Q8C3bdcQTMkyjYGd3 https://id.oclc.org/worldcat/ontology/hasWork Print version: Data intensive computing applications for big data. Amsterdam, Netherlands : IOS Press, 2018 1614998132 9781614998136 (OCoLC)1027348597 Advances in parallel computing ; v. 29. http://id.loc.gov/authorities/names/n88500108 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1791224 Volltext |
| spellingShingle | Data intensive computing applications for big data / Advances in parallel computing ; 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. 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. 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. Blockchain Innovation and Its Impact on Business Banking OperationsSubject Index; Author Index. Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Données volumineuses. COMPUTERS Databases Data Warehousing. bisacsh Big data fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh2012003227 |
| title | Data intensive computing applications for big data / |
| title_auth | Data intensive computing applications for big data / |
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| title_full | Data intensive computing applications for big data / edited by Mamta Mittal, Valentina E. Balas, D. Jude Hemanth, and Raghvendra Kumar. |
| title_fullStr | Data intensive computing applications for big data / edited by Mamta Mittal, Valentina E. Balas, D. Jude Hemanth, and Raghvendra Kumar. |
| title_full_unstemmed | Data intensive computing applications for big data / edited by Mamta Mittal, Valentina E. Balas, D. Jude Hemanth, and Raghvendra Kumar. |
| title_short | Data intensive computing applications for big data / |
| title_sort | data intensive computing applications for big data |
| topic | Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Données volumineuses. COMPUTERS Databases Data Warehousing. bisacsh Big data fast |
| topic_facet | Big data. Données volumineuses. COMPUTERS Databases Data Warehousing. Big data |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1791224 |
| work_keys_str_mv | AT mittalmamta dataintensivecomputingapplicationsforbigdata AT balasvalentinaemilia dataintensivecomputingapplicationsforbigdata AT hemanthdjude dataintensivecomputingapplicationsforbigdata AT kumarraghvendra dataintensivecomputingapplicationsforbigdata |