Data mining case study: modeling the behavior of offenders who commit serious sexual assaults
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting meaningful entities from police narrative reports
dg.o '02 Proceedings of the 2002 annual national conference on Digital government research
COPLINK: visualization for crime analysis
dg.o '03 Proceedings of the 2003 annual national conference on Digital government research
Visualizing criminal relationships: comparison of a hyperbolic tree and a hierarchical list
Decision Support Systems
Temporal extrapolation within a static clustering
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
A distance measure for determining similarity between criminal investigations
ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining
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Dismantling networks of career criminals is one of the focus points of modern police forces. A key factor within this area of law enforcement is the accumulation of delinquents at the bottom of the criminal hierarchy. A deployed early warning system could benefit the cause by supplying an automated alarm after every apprehension, sounding when this perpetrator is likely to become a career criminal. Such a system can easily be built upon existing, strategic, analysis already performed at headquarters. We propose a tool that superimposes a 2-dimensional extrapolation on a static clustering, that describes the movement in time of an offender through the criminal spectrum. Using this extrapolation, possible future attributes are calculated and the criminal is classified accordingly. If the predicted class falls within the danger category, the system notifies police officials. We outline the implementation of such a tool and highlight test results on the Dutch National Criminal Record Database. Certain problematic situations, like time constraints, privacy concerns and reliability issues, are also discussed.