Data Intensive Computing Applications for Big Data.
Material type:
- text
- computer
- online resource
- 9781614998143
- 005.7
- QA76.9.B45 .D383 2018
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 Learning -- A 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 Applications -- Accurate 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 Operations -- Subject Index -- Author Index.
Description based on publisher supplied metadata and other sources.
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
There are no comments on this title.