
Big Data Analytics
Description
Key Features
- Review of big data research challenges from diverse areas of scientific endeavor
- Rich perspective on a range of data science issues from leading researchers
- Insight into the mathematical and statistical theory underlying the computational methods used to address big data analytics problems in a variety of domains
Readership
Computer scientists, statisticians, data scientists, and Artificial Intelligence researchers
Table of Contents
A: Modeling and Analytics
Chapter 1: Document Informatics for Scientific Learning and Accelerated Discovery
- Abstract
- 1 Introduction
- 2 How Document Informatics Will Aid Materials Discovery
- 3 The General Research Framework
- 4 Pilot Implementation
Chapter 2: An Introduction to Rare Event Simulation and Importance Sampling
- Abstract
- 1 Introduction: Monte Carlo Methods, Rare Event Simulation, and Variance Reduction Techniques
- 2 MC Methods and the Problem of Rare Events
- 3 Importance Sampling
- 4 Multiple IS
- 5 The Cross-Entropy Method
- 6 MCMC: Rejection Sampling, the Metropolis Method, and Gibbs Sampling
- 7 Applications of VRTs to Error Estimation in Optical Fiber Communication Systems
- 8 Large Deviations Theory, Asymptotic Efficiency, and Final Remarks
Chapter 3: A Large-Scale Study of Language Usage as a Cognitive Biometric Trait
- Abstract
- 1 Introduction
- 2 Cognitive Fingerprints: Problem Description
- 3 Data Description
- 4 Methodology
- 5 Results
- 6 Discussions
- 7 Related Work
- 8 Conclusions and Future Work
- Acknowledgment
Chapter 4: Customer Selection Utilizing Big Data Analytics
- Abstract
- 1 Introduction
- 2 Methodology
- 3 Experiments
- 4 Conclusion
Chapter 5: Continuous Model Selection for Large-Scale Recommender Systems
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Preference Prediction
- 4 Proposed Continuous Modeling
- 5 Experimental Evaluations
- 6 Conclusion and Future Work
Chapter 6: Zero-Knowledge Mechanisms for Private Release of Social Graph Summarization
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Graph Summarization
- 4 Background on ε-Zero-Knowledge Privacy
- 5 ZKP Mechanism for Graph Summarization
- 6 Evaluation
- 7 From Privacy Level to Noise Scale
- 8 Private Probabilistic A-GS
- 9 Conclusions
Chapter 7: Distributed Confidence-Weighted Classification on Big Data Platforms
- Abstract
- 1 Introduction
- 2 Classification with Linear SVM Models
- 3 MapReduce Framework for Distributed Computations
- 4 CW Classification Using MapReduce
- 5 Experiments
- 6 Conclusion
- Acknowledgments
B: Applications and Infrastructure
Chapter 8: Big Data Applications in Health Sciences and Epidemiology
- Abstract
- 1 Introduction
- 2 Mathematical Framework for Epidemiology
- 3 Dynamics and Analysis Problems
- 4 Inference Problems
- 5 Disease Surveillance, Molecular Epidemiology, and Pathogen Phylodynamics
- 6 High-Performance Synthetic Information Environments and Tools
- 7 Summary
- Acknowledgments
Chapter 9: Big Data Driven Natural Language Processing Research and Applications
- Abstract
- 1 Introduction
- 2 NLP Core Tasks
- 3 NLP Applications
- 4 Data Sources for NLP Research
- 5 Big Data Driven NLP Research and Applications
- 6 Trends and Future Research Directions
- 7 Conclusions
Chapter 10: Analyzing Big Spatial and Big Spatiotemporal Data: A Case Study of Methods and Applications
- Abstract
- 1 Introduction
- 2 Algorithms
- 3 Applications
- 4 Conclusions
Chapter 11: Experimental Computational Simulation Environments for Big Data Analytic in Social Sciences
- Abstract
- 1 Introduction
- 2 Big Data Analytics
- 3 Sociofinancial-Economic Simulations
- 4 Software Infrastructure for Social Sciences
- 5 Market Simulators for Financial Economics Modeling
- 6 Statistical Simulations of AT Models
- 7 DRACUS
- 8 Summary
Chapter 12: Terabyte-Scale Image Similarity Search
- Abstract
- 1 Introduction
- 2 Big-Data Processing
- 3 Application Workload (Distributed Indexing + Searching)
- 4 Hadoop in Practice
- 5 Large-Scale Hadoop
- 6 Conclusion
- Acknowledgments
Chapter 13: Measuring Inter-site Engagement in a Network of Sites
- Abstract
- 1 Introduction
- 2 Related Work
- 3 Data, Networks, and Metrics
- 4 Evaluating Inter-site Metrics
- 5 Studying Inter-site Engagement
- 6 The Network Effect
- 7 Hyperlink Performance
- 8 Conclusions
- 9 Future Work
- Acknowledgments
Chapter 14: Scaling RDF Triple Stores in Size and Performance: Modeling SPARQL Queries as Graph Homomorphism Routines
- Abstract
- 1 Introduction
- 2 SPARQL Queries as Graph Homomorphism Routines
- 3 GEMS: Graph Database Engine for Multithreaded Systems
- 4 Related Work
- 5 Experimental Results
- 6 Conclusions
Product details
- No. of pages: 390
- Language: English
- Copyright: © North Holland 2015
- Published: July 7, 2015
- Imprint: North Holland
- Hardcover ISBN: 9780444634924
- eBook ISBN: 9780444634979
About the Series Volume Editors
Venu Govindaraju
