You are previewing Geo-Intelligence and Visualization through Big Data Trends.
O'Reilly logo
Geo-Intelligence and Visualization through Big Data Trends

Book Description

The last decade has seen a tremendous increase in the volume of data collected from personal and professional sources. While there have been many computational approaches available for analyzing these datasets, there is also growing interest in visualizing and making sense of spatio-temporal data. Geo-Intelligence and Visualization through Big Data Trends provides an overview of recent developments, applications, and research on the topic of spatio-temporal big data analysis and visualization, as well as location intelligence and analytics. Focusing on emerging trends in this dynamic field, this publication is an innovative resource aimed at the scholarly and professional interests of academicians, practitioners, and students.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
    1. Mission
    2. Coverage
  5. Foreword
  6. Preface
    1. REFERENCES
  7. Chapter 1: Analysis of Mobile Phone Call Data of Istanbul Residents
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. METHODOLOGY
    5. FINDINGS
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. REFERENCES
    9. KEY TERMS AND DEFINITIONS
  8. Chapter 2: Campaign Optimization through Mobility Network Analysis
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. CHARACTERIZATION OF A CAMPAIGN
    5. OPTIMIZED CAMPAIGNS
    6. CAMPAIGN OPTIMIZATION USING REAL-WORLD MOBILITY NETWORKS
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
    9. REFERENCES
    10. KEY TERMS AND DEFINITIONS
    11. ENDNOTES
  9. Chapter 3: Assessing Financial Well-Being of Merchants by Analyzing Behavioral Patterns in Historical Transactions
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. METHODOLOGY
    5. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
    6. REFERENCES
    7. KEY TERMS AND DEFINITIONS
  10. Chapter 4: The Role of Geo-Demographic Big Data for Assessing the Effectiveness of Crowd-Funded Software Projects
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. A GEO-DEMOGRAPHIC ANALYSIS OF BIG DATA CONNECTED WITH ADVERTISING OF CROWD-FUNDING PROJECTS THROUGH THE CONTEMPORARY PRISM OF INTERNET TROLLING
    5. GENERALISING THE DATA
    6. IMPLICATIONS AND FUTURE RESEARCH DIRECTIONS
    7. DISCUSSION
    8. REFERENCES
    9. KEY TERMS AND DEFINITIONS
  11. Chapter 5: An Interactive Tool for Visualizing and Analyzing Spatio-Temporal Data
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. METHODOLOGY
    5. ANALYSIS AND RESULTS
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. ACKNOWLEDGMENT
    9. REFERENCES
    10. KEY TERMS AND DEFINITIONS
  12. Chapter 6: Building a Visual Analytics Tool for Location-Based Services
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. DOMAIN PROBLEM SPECIFICATION
    5. EXPERIMENT
    6. DISCUSSION
    7. CONCLUSION
    8. REFERENCES
    9. KEY TERMS AND DEFINITIONS
  13. Chapter 7: Data Visualization Using Weighted Voronoi Diagrams
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. SOLVING PROBLEM 1
    5. COMPUTATIONAL RESULTS
    6. CONCLUSION
    7. FUTURE RESEARCH DIRECTIONS
    8. REFERENCES
    9. KEY TERMS AND DEFINITIONS
  14. Chapter 8: Developing a Method for Visualizing Population Movements
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. GENERAL VISUALIZATION TECHNIQUES FOR GEOGRAPHIC MOVEMENT
    5. DEVELOPING A VISUALIZATION METHOD FOR POPULATION MOVEMENTS
    6. RESULTS
    7. CONCLUSION AND FURTHER RESEARCH
    8. REFERENCES
    9. KEY TERMS AND DEFINITIONS
  15. Chapter 9: Care to Share?
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. MATHEMATICAL MODELING
    5. DYNAMIC RIDE SHARING HEURISTICS
    6. DISCUSSION
    7. STATIC RIDE SHARING AND SHAREABILITY NETWORKS
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
    10. ACKNOWLEDGMENT
    11. REFERENCES
    12. KEY TERMS AND DEFINITIONS
    13. ENDNOTES
  16. Chapter 10: SPAM
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. SpaGrid: A SPATIAL GRID FRAMEWORK FOR HIGH DIMENSIONAL DATABASES
    5. IMPLEMENTATION
    6. EXPERIMENTAL ANALYSIS
    7. CONCLUSION AND FUTURE WORKS
    8. REFERENCES
    9. KEY TERMS AND DEFINITIONS
  17. Chapter 11: Demystifying Big Data in the Cloud
    1. ABSTRACT
    2. INTRODUCTION
    3. BIG DATA IN THE CLOUD AND SECURITY
    4. DATA MINING AS DRIVING CLOUD SECURITY ADOPTION
    5. BIG DATA PLUMBING PROBLEMS HINDER CLOUD COMPUTING
    6. BIG DATA FOR OPTIMAL CLOUD PERFORMANCE AND SECURITY
    7. DATA MINING SECURITY ISSUES IN THE DATA CLOUD
    8. BIG DATA IN THE CLOUD VISUALIZATIONS AND APPS
    9. BIG DATA IN THE CLOUD FUTURE TRENDS AND CHALLENGES
    10. CONCLUSION
    11. ACKNOWLEDGMENT
    12. REFERENCES
    13. KEY TERMS AND DEFINITIONS
  18. Compilation of References
  19. About the Contributors