Big Data Analytics: Methods and Applications

Book Overview

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.

• Format: Paperback
• Language: English
• ISBN: 8132238710
• ISBN13: 9788132238713
• Release Date: June 2018
• Publisher: Springer
• Length: 276 Pages
• Weight: 0.90 lbs.
• Dimensions: 0.6" x 6.1" x 9.2"