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Surveillance Technologies and Early Warning Systems

Book Description

The modern world is fraught with risk, from natural disasters and terrorist attacks, to financial crises and pandemics. Assessing and planning for these risks can be done with a conventional human-based approach but this often requires large amounts of time and resources. Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection has never been more important, as the research this book presents an alternative to conventional surveillance and risk assessment. This book is a multidisciplinary excursion comprised of data mining, early warning systems, information technologies and risk management and explores the intersection of these components in problematic domains. It offers the ability to apply the most modern techniques to age old problems allowing for increased effectiveness in the response to future, eminent, and present risk.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
    2. List of Reviewers
  5. Foreword
  6. Preface
  7. Acknowledgment
  8. Section 1: Theoretical and Conceptual Approach to Early Warning Systems
    1. Chapter 1: Overview of Knowledge Discovery in Databases Process and Data Mining for Surveillance Technologies and EWS
      1. Abstract
      2. INTRODUCTION
      3. SOME DATA MINING APPLICATIONS FOR EWS DEVELOPMENT IN THE LITERaTURE
      4. KNOWLEDGE DISCOVERY IN DATABASES process AND DATA MINING
      5. MINING ADVANCED DATA TYPES
      6. DM Software Used in EWS
      7. FuTURE rESEARCH dIRECTIONS
      8. Conclusion
    2. Chapter 2: Data Mining and Privacy Protection
      1. Abstract
      2. INTRODUCTION
      3. Background
      4. PRIVACY PROTECTION HISTORY AND DEVELOPMENT
      5. FuTURE rESEARCH dIRECTIONS
      6. Conclusion
    3. Chapter 3: On the Nature and Scales of Statistical Estimations Divergence and its Linkage with Statistical Learning
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN THRUST
      5. THE GAP BETWEEN ESTIMATIONS AND REALIZATIONS WITH NUMERICAL EXAMPLES
      6. CONCLUSION AND FUTURE STUDIES
    4. Chapter 4: Black-Necked Swans and Active Risk Management
      1. ABSTRACT
      2. Introduction
      3. MEASURES OF FINANCIAL RISKS AND THE BASEL ACCORD
      4. Sequential Detection and Surveillance
      5. Probability Estimates for Early Warning of Impending Adversity
      6. Conclusion
  9. Section 2: Early Warning Systems for Finance
    1. Chapter 5: Financial Early Warning System for Risk Detection and Prevention from Financial Crisis
      1. Abstract
      2. INTRODUCTION
      3. SMEs and FINANCIAL ISSUES
      4. THE IMPACT OF FINANCIAL CRISIS on SMEs
      5. A Solution for SMEs: EARLY WARNING SYSTEM
      6. DATA MINING MODEL and AN IMPLEMENTATION for EARLY WARNING SYSTEM
      7. CONCLUSION
    2. Chapter 6: Designing an Early Warning System for Stock Market Crashes by Using ANFIS
      1. Abstract
      2. INTRODUCTION
      3. Background
      4. MATERIAL AND METHODS
      5. BENCHMARKING DATA MINING METHODS
      6. RESULTS
      7. FUTURE RESEARCH DIRECTIONS
      8. Conclusion
    3. Chapter 7: Bankruptcy Prediction by Supervised Machine Learning Techniques
      1. ABSTRACT
      2. INTRODUCTION
      3. LITERATURE REVIEW
      4. EXPERIMENTAL SETUP
      5. EXPERIMENTAL RESULTS
      6. CONCLUSION
    4. Chapter 8: Data Mining Used for Analyzing the Bankruptcy Risk of the Romanian SMEs
      1. Abstract
      2. INTRODUCTION
      3. Background
      4. Using Data Mining for analyzing the bankruptcy risk of the Romanian SMEs
      5. FuTURE rESEARCH dIRECTIONS
      6. Conclusion
  10. Section 3: Early Warning Systems for Detection and Prevention of Fraud, Crime, Money Laundering and Terrorist Financing
    1. Chapter 9: Social Aid Fraud Detection System and Poverty Map Model Suggestion Based on Data Mining for Social Risk Mitigation
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. SOCIAL AID FRAUD DETECTION SYSTEM FOR SOCIAL RISK MITIGATION
      5. METHODS
      6. SOCIAL AID FRAUD DETECTION SYSTEM AND POVERTY MAP
      7. CONCLUSION
    2. Chapter 10: Collaborative Video Surveillance for Distributed Visual Data Mining of Potential Risk and Crime Detection
      1. Abstract
      2. INTRODUCTION
      3. Background
      4. CVS-DVDM of Potential Risk and Crime Detection
      5. FuTURE rESEARCH dIRECTIONS
      6. Conclusion
    3. Chapter 11: Data Mining and Economic Crime Risk Management
      1. Abstract
      2. INTRODUCTION
      3. Background
      4. Application of data mining for economic crime risk management
      5. Solutions and Recommendations Academic Research
      6. FuTURE rESEARCH dIRECTIONS
      7. Conclusion
    4. Chapter 12: Data Mining in the Investigation of Money Laundering and Terrorist Financing
      1. Abstract
      2. INTRODUCTION
      3. Background
      4. Data Mining Process
      5. Solution
      6. Future work
      7. Conclusion
  11. Section 4: Early Warning Systems for Customer Services and Marketing
    1. Chapter 13: Data Mining and Explorative Multivariate Data Analysis for Customer Satisfaction Study
      1. Abstract
      2. INTRODUCTION
      3. ORDERED MULTIPLE CORRESPONDENCE ANALYSIS TO STUDY CS VARIABLE INTERRELATIONSHIPS
      4. BOOSTING REGRESSION TECHNIQUES
      5. LINEAR AND NON-LINEAR PLS
      6. DISCRIMINANT PARTIAL LEAST SQUARES REGRESSION MODELS AND SOME EXTENSIONS TOWARDS MULTIVARIATE ADDITIVE MODELS
      7. CONCLUSION
      8. Appendix
    2. Chapter 14: Using POS Data for Price Promotions Evaluation
      1. ABSTRACT
      2. INTRODUCTION
      3. PRICE PROMOTIONS – STATE OF THE ART
      4. FUTURE RESEARCH
      5. CONCLUSION
  12. Compilation of References
  13. About the Contributors