Intelligent Data Analysis

Intelligent Data Analysis

by Deepak Gupta, Siddhartha Bhattacharyya, Ashish Khanna, Kalpna Sagar
Released July 2020
Publisher(s): Wiley
ISBN: 9781119544456

Read it now on the O’Reilly learning platform with a 10-day free trial.

O’Reilly members get unlimited access to books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.

Start your free trial

Book description


This book focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension, and emphasis will also be given to solving of problems which result from automated data collection, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and so on. This book aims to describe the different approaches of Intelligent Data Analysis from a practical point of view: solving common life problems with data analysis tools.

Table of contents

  1. Cover
  2. List of Contributors
  3. Series Preface
  4. Preface
  5. 1 Intelligent Data Analysis: Black Box Versus White Box Modeling
    1. 1.1 Introduction
    2. 1.2 Interpretation of White Box Models
    3. 1.3 Interpretation of Black Box Models
    4. 1.4 Issues and Further Challenges
    5. 1.5 Summary
    6. References
  6. 2 Data: Its Nature and Modern Data Analytical Tools
    1. 2.1 Introduction
    2. 2.2 Data Types and Various File Formats
    3. 2.3 Overview of Big Data
    4. 2.4 Data Analytics Phases
    5. 2.5 Data Analytical Tools
    6. 2.6 Database Management System for Big Data Analytics
    7. 2.7 Challenges in Big Data Analytics
    8. 2.8 Conclusion
    9. References
  7. 3 Statistical Methods for Intelligent Data Analysis: Introduction and Various Concepts
    1. 3.1 Introduction
    2. 3.2 Probability
    3. 3.3 Descriptive Statistics
    4. 3.4 Inferential Statistics
    5. 3.5 Statistical Methods
    6. 3.6 Errors
    7. 3.7 Conclusion
    8. References
  8. 4 Intelligent Data Analysis with Data Mining: Theory and Applications
    1. 4.1 Introduction to Data Mining
    2. 4.2 Data and Knowledge
    3. 4.3 Discovering Knowledge in Data Mining
    4. 4.4 Data Analysis and Data Mining
    5. 4.5 Data Mining: Issues
    6. 4.6 Data Mining: Systems and Query Language
    7. 4.7 Data Mining Methods
    8. 4.8 Data Exploration
    9. 4.9 Data Visualization
    10. 4.10 Probability Concepts for Intelligent Data Analysis (IDA)
    11. Reference
  9. 5 Intelligent Data Analysis: Deep Learning and Visualization
    1. 5.1 Introduction
    2. 5.2 Deep Learning and Visualization
    3. 5.3 Data Processing and Visualization
    4. 5.4 Experiments and Results
    5. 5.5 Conclusion
    6. References
  10. 6 A Systematic Review on the Evolution of Dental Caries Detection Methods and Its Significance in Data Analysis Perspective
    1. 6.1 Introduction
    2. 6.2 Different Caries Lesion Detection Methods and Data Characterization
    3. 6.3 Technical Challenges with the Existing Methods
    4. 6.4 Result Analysis
    5. 6.5 Conclusion
    6. Acknowledgment
    7. References
  11. 7 Intelligent Data Analysis Using Hadoop Cluster – Inspired MapReduce Framework and Association Rule Mining on Educational Domain
    1. 7.1 Introduction
    2. 7.2 Learning Analytics in Education
    3. 7.3 Motivation
    4. 7.4 Literature Review
    5. 7.5 Intelligent Data Analytical Tools
    6. 7.6 Intelligent Data Analytics Using MapReduce Framework in an Educational Domain
    7. 7.7 Results
    8. 7.8 Conclusion and Future Scope
    9. References
  12. 8 Influence of Green Space on Global Air Quality Monitoring: Data Analysis Using K-Means Clustering Algorithm
    1. 8.1 Introduction
    2. 8.2 Material and Methods
    3. 8.3 Results
    4. 8.4 Quantitative Analysis
    5. 8.5 Discussion
    6. 8.6 Conclusion
    7. References
  13. 9 IDA with Space Technology and Geographic Information System
    1. 9.1 Introduction
    2. 9.2 Geospatial Techniques
    3. 9.3 Comparative Analysis
    4. 9.4 Conclusion
    5. References
  14. 10 Application of Intelligent Data Analysis in Intelligent Transportation System Using IoT
    1. 10.1 Introduction to Intelligent Transportation System (ITS)
    2. 10.2 Issues and Challenges of Intelligent Transportation System (ITS)
    3. 10.3 Intelligent Data Analysis Makes an IoT-Based Transportation System Intelligent
    4. 10.4 Intelligent Data Analysis for Security in Intelligent Transportation System
    5. 10.5 Tools to Support IDA in an Intelligent Transportation System
    6. References
  15. 11 Applying Big Data Analytics on Motor Vehicle Collision Predictions in New York City
    1. 11.1 Introduction
    2. 11.2 Materials and Methods
    3. 11.3 Classification Algorithms and K-Fold Validation Using Data Set Obtained from NYPD (2012–2017)
    4. 11.4 Results
    5. 11.5 Discussion
    6. 11.6 Conclusion
    7. References
  16. 12 A Smart and Promising Neurological Disorder Diagnostic System: An Amalgamation of Big Data, IoT, and Emerging Computing Techniques
    1. 12.1 Introduction
    2. 12.2 Statistics of Neurological Disorders
    3. 12.3 Emerging Computing Techniques
    4. 12.4 Related Works and Publication Trends of Articles
    5. 12.5 The Need for Neurological Disorders Diagnostic System
    6. 12.6 Conclusion
    7. References
  17. 13 Comments-Based Analysis of a Bug Report Collection System and Its Applications
    1. 13.1 Introduction
    2. 13.2 Background
    3. 13.3 Related Work
    4. 13.4 Data Collection Process
    5. 13.5 Analysis of Bug Reports
    6. 13.6 Threats to Validity
    7. 13.7 Conclusion
    8. References
    9. Notes
  18. 14 Sarcasm Detection Algorithms Based on Sentiment Strength
    1. 14.1 Introduction
    2. 14.2 Literature Survey
    3. 14.3 Experiment
    4. 14.4 Results and Evaluation
    5. 14.5 Conclusion
    6. References
    7. Notes
  19. 15 SNAP: Social Network Analysis Using Predictive Modeling
    1. 15.1 Introduction
    2. 15.2 Literature Survey
    3. 15.3 Comparative Study
    4. 15.4 Simulation and Analysis
    5. 15.5 Conclusion and Future Work
    6. References
  20. 16 Intelligent Data Analysis for Medical Applications
    1. 16.1 Introduction
    2. 16.2 IDA Needs in Medical Applications
    3. 16.3 IDA Methods Classifications
    4. 16.4 Intelligent Decision Support System in Medical Applications
    5. 16.5 Conclusion
    6. References
  21. 17 Bruxism Detection Using Single-Channel C4-A1 on Human Sleep S2 Stage Recording
    1. 17.1 Introduction
    2. 17.2 History of Sleep Disorder
    3. 17.3 Electroencephalogram Signal
    4. 17.4 EEG Data Measurement Technique
    5. 17.5 Literature Review
    6. 17.6 Subjects and Methodology
    7. 17.7 Data Analysis of the Bruxism and Normal Data Using EEG Signal
    8. 17.8 Result
    9. 17.9 Conclusions
    10. Acknowledgments
    11. References
  22. 18 Handwriting Analysis for Early Detection of Alzheimer's Disease
    1. 18.1 Introduction and Background
    2. 18.2 Proposed Work and Methodology
    3. 18.3 Results and Discussions
    4. 18.4 Conclusion
    5. References
  23. Index
  24. End User License Agreement

Product information

  • Title: Intelligent Data Analysis
  • Author(s): Deepak Gupta, Siddhartha Bhattacharyya, Ashish Khanna, Kalpna Sagar
  • Release date: July 2020
  • Publisher(s): Wiley
  • ISBN: 9781119544456