Big Data Analytics Methods and Applications
This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover t...
| Other Authors: | , , |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
New Delhi
Springer India
2016, 2016
|
| Edition: | 1st ed. 2016 |
| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Chapter 1. Introduction: The Promises and Challenges of Big Data Analytics
- Chapter 2. Massive Data Analysis: Tasks, Tools, Applications and Challenges
- Chapter 3. Statistical Challenges with Big Data in Management Science
- Chapter 4. Application of Mixture Models to Large Datasets
- Chapter 5. An Efficient Partition-Repetition Approach in Clustering of Big Data
- Chapter 6. Multithreaded Graph Algorithms for Large-scale Analytics
- Chapter 7. On-line Graph Partitioning with an Affine Message Combining Cost Function
- Chapter 8. Big Data Analytics Platforms for Real-time Applications in IoT
- Chapter 9. Complex Event Processing in Big Data Systems
- Chapter 10. Unwanted Traffic Identification in Large-scale University Networks: A Case Study
- Chapter 11. Application-Level Benchmarking of Big Data Systems
- Chapter 12. Managing Large Scale Standardized Electronic Healthcare Records
- Chapter 13. Microbiome Data Mining for Microbial Interactions and Relationships
- Chapter 14. A Nonlinear Technique for Analysis of Big Data in Neuroscience
- Chapter 15. Big Data and Cancer Research