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Data Mining and Predictive Analysis

Author Colleen McCue
Release Date: 2006/09/01
ISBN: 9780750677967
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Book Description

It is now possible to predict the future when it comes to crime. In Data Mining and Predictive Analysis, Dr. Colleen McCue describes not only the possibilities for data mining to assist law enforcement professionals, but also provides real-world examples showing how data mining has identified crime trends, anticipated community hot-spots, and refined resource deployment decisions. In this book Dr. McCue describes her use of "off the shelf" software to graphically depict crime trends and to predict where future crimes are likely to occur. Armed with this data, law enforcement executives can develop "risk-based deployment strategies," that allow them to make informed and cost-efficient staffing decisions based on the likelihood of specific criminal activity.

Knowledge of advanced statistics is not a prerequisite for using Data Mining and Predictive Analysis. The book is a starting point for those thinking about using data mining in a law enforcement setting. It provides terminology, concepts, practical application of these concepts, and examples to highlight specific techniques and approaches in crime and intelligence analysis, which law enforcement and intelligence professionals can tailor to their own unique situation and responsibilities.

* Serves as a valuable reference tool for both the student and the law enforcement professional
* Contains practical information used in real-life law enforcement situations
* Approach is very user-friendly, conveying sophisticated analyses in practical terms

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Dedication
  5. Foreword
  6. Preface
  7. Introduction
  8. Table of Contents
  9. Part 1: Introductory Section
    1. Chapter 1: Basics
    2. Chapter 2: Domain Expertise
    3. Chapter 3: Data Mining
  10. Part 2: Methods
    1. Chapter 4: Process Models for Data Mining and Analysis
    2. Chapter 5: Data
    3. Chapter 6: Operationally Relevant Preprocessing
    4. Chapter 7: Predictive Analytics
    5. Chapter 8: Public Safety-Specific Evaluation
    6. Chapter 9: Operationally Actionable Output
  11. Part 3: Applications
    1. Chapter 10: Normal Crime
    2. Chapter 11: Behavioral Analysis of Violent Crime
    3. Chapter 12: Risk and Threat Assessment
  12. Part 4: Case Examples
    1. Chapter 13: Deployment
    2. Chapter 14: Surveillance Detection
  13. Part 5: Advanced Concepts and Future Trends
    1. Chapter 15: Advanced Topics
    2. Chapter 16: Future Trends
  14. Index
  15. Instructions for online access
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