Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis

Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis, 2nd Edition, describes clearly and simply how crime clusters and other intelligence can be used to deploy security resources most effectively. Rather than being reactive, security agencies can anticipate and prevent crime through the appropriate application of data mining and the use of standard computer programs. Data Mining and Predictive Analysis offers a clear, practical starting point for professionals who need to use data mining in homeland security, security analysis, and operational law enforcement settings. This revised text highlights new and emerging technology, discusses the importance of analytic context for ensuring successful implementation of advanced analytics in the operational setting, and covers new analytic service delivery models that increase ease of use and access to high-end technology and analytic capabilities. The use of predictive analytics in intelligence and security analysis enables the development of meaningful, information based tactics, strategy, and policy decisions in the operational public safety and security environment.

Discusses new and emerging technologies and techniques, including up-to-date information on predictive policing, a key capability in law enforcement and securityDemonstrates the importance of analytic context beyond softwareCovers new models for effective delivery of advanced analytics to the operational environment, which have increased access to even the most powerful capabilitiesIncludes terminology, concepts, practical application of these concepts, and examples to highlight specific techniques and approaches in crime and intelligence analysis

Introductory Section
Chapter 1: Basics
Chapter 2: Domain Expertise
Chapter 3: Data mining

Methods
Chapter 4: Process Models for Data Mining and Analysis
Chapter 5: Data
Chapter 6: Operationally-relevant preprocessing
Chapter 7: Identification, Characterization and Modeling
Chapter 8: Evaluation
Chapter 9: Operationally-Actionable Output

Applications
Chapter 10: “Normal” Crime
Chapter 11: Behavioral Analysis of Violent Crime
Chapter 12: Risk and Threat Assessment

Case Examples
Chapter 13: Deployment
Chapter 14: Surveillance Detection

Advanced Concepts and Future Trends
Chapter 15: Advanced Concepts in Data Mining
Chapter 16: Future Trends