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DATA MINING AND PREDICTIVE ANALYSIS: INTELLIGENCE GATHERING AND CRIME ANALYSIS 2E
Título:
DATA MINING AND PREDICTIVE ANALYSIS: INTELLIGENCE GATHERING AND CRIME ANALYSIS 2E
Subtítulo:
Autor:
MCCUE, C
Editorial:
ACADEMIC PRESS
Año de edición:
2015
ISBN:
978-0-12-800229-2
Páginas:
422
61,50 € -10,0% 55,35 €

 

Sinopsis

´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, includingup-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 capabilities Includes terminology, concepts, practical application of these concepts, and examples to highlight specific techniques and approaches in crime and intelligence analysis´



Table of Contents:
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´