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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.
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.
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