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Twenty-four/Seven Crime Analysis: Web-based Data Mining, Predictive Analytics

NCJ Number
204500
Journal
Law Enforcement Technology Volume: 31 Issue: 2 Dated: February 2004 Pages: 92,94,99
Author(s)
Colleen McCue; Andre Parker
Editor(s)
Ronnie Garrett
Date Published
February 2004
Length
7 pages
Annotation
This article describes the use of data mining and predictive analytics in the field of law enforcement and crime analysis focusing on the Richmond (Virginia) Police Department.
Abstract
Challenging law enforcement and intelligence analysis is the ever increasing amount of data now available for analysis. The challenge continues since most data and information analyzed are collected for some other purpose. However, data mining and predictive analytic tools have allowed law enforcement to move from counting crime to actually predicting it. Recently, data mining tools have been deployed in the Web environment to be used where needed. The Richmond (Virginia) Police Department has exploited the visual and highly intuitive aspects of data mining, using information and analysis as an interface between the analytical and operational personnel. With Web-based data mining tools, analysis can be when and where the operational personnel need it. The Richmond Police Department has explored the use of Web-based mining tools for risk assessment and motive determination. Data mining tools afford the opportunity to determine what information is likely to be important early in an investigation and what can wait. Web-based analytics allows law enforcement organizations to fully exploit their analytical capacity. In order to properly deploy their resources, modern law enforcement must have the ability to mine critical information in real time.

Publication Format
Article
Publication Type
Research (Applied/Empirical)
Language
English
Country
United States of America