Data Mining and Predictive Analysis (häftad)
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Format
Häftad (Paperback)
Språk
Engelska
Antal sidor
368
Utgivningsdatum
2006-10-01
Upplaga
illustrated ed
Förlag
Butterworth-Heinemann
Illustrationer
1
Dimensioner
236 x 190 x 22 mm
Vikt
860 g
Antal komponenter
1
Komponenter
50:B&W 7.44 x 9.69 in or 246 x 189 mm (Crown 4vo) Perfect Bound on White w/Gloss Lam
ISBN
9780750677967

Data Mining and Predictive Analysis

Intelligence Gathering and Crime Analysis

av Colleen McCue
Häftad,  Engelska, 2006-10-01
890
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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
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Recensioner i media

"[Data Mining and Predictive Analysis] is a must-read..., blending analytical horsepower with real-life operational examples. Operators owe it to themselves to dig in and make tactical decisions more efficiently, and learn the language that sells good tactics to leadership. Analysts, intell support, and leaders owe it to themselves to learn a new way to attack the problem in support of law enforcement, security, and intelligence operations. Not just a dilettante academic, Dr. McCue is passionate about getting the best tactical solution in the most efficient way-and she uses data mining to do it. Understandable yet detailed, [Data Mining and Predictive Analysis] puts forth a solid argument for integrating predictive analytics into action. Not just for analysts!" --Tim King (Director, Special Programs and Global Business Development, ArmorGroup International Training)

Övrig information

Dr. Colleen McCue is the Senior Director of Social Science and Quantitative Methods at DigitalGlobe. Her areas of expertise within , in the applied public safety and national security environment include the application of data mining and predictive analytics to the analysis of crime and intelligence data, with particular emphasis on deployment strategies; surveillance detection; threat and vulnerability assessment; geospatial predictive analytics; computational modeling and visualization of human behavior; Human, Social, Culture and Behavior (HSCB) modeling and analysis; crisis and conflict mapping; and the behavioral analysis of violent crime in support of anticipation and influence.

Innehållsförteckning

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

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