Data Mining and Predictive Analysis
Intelligence Gathering and Crime Analysis
- 422 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About This Book
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 inhomeland security, security analysis, and operational law enforcementsettings. This revised text highlights new and emerging technology, discusses the importance of analytic contextfor 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 inintelligence and securityanalysis 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 security
- Demonstrates the importance of analytic context beyond software
- Covers new models for effective delivery of advanced analytics to the operational environment, which have increased access to even the most powerful capabilities
- Includes terminology, concepts, practical application of these concepts, and examples to highlight specific techniques and approaches in crime and intelligence analysis
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Information
Table of contents
- Cover
- Title page
- Table of Contents
- Copyright
- Dedication
- Foreword
- Preface
- Digital Assets
- Introduction
- Part 1: Introductory Section
- Part 2: Methods
- Part 3: Applications
- Part 4: Case Examples
- Part 5: Advanced Concepts and Future Trends
- Index