A decision model for spatial site selection by criminals: a foundation for law enforcement decision support

Authors:
Yifei Xue;D. E. Brown
Affiliations:
Dept. of Syst. & Inf. Eng., Univ. of Virginia, Charlottesville, VA, USA;-
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Year:
2003

Citing 0
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Spatial analysis with preference specification of latent decision makers for criminal event prediction

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EFFECTIVENESS OF SUPPORT VECTOR MACHINE FOR CRIME HOT-SPOTS PREDICTION

Applied Artificial Intelligence
Computational Modeling of Criminal Activity

EuroISI '08 Proceedings of the 1st European Conference on Intelligence and Security Informatics
Spatial analysis with preference specification of latent decision makers for criminal event prediction

Decision Support Systems - Special issue: Intelligence and security informatics
An intelligent decision-support model using FSOM and rule extraction for crime prevention

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Abstract

Crime analysis uses past crime data to predict future crime locations and times. Typically this analysis relies on hot spot models that show clusters of criminal events based on past locations of these events. It does not consider the decision making processes of criminals as human initiated events susceptible to analysis using spatial choice models. This paper analyzes criminal incidents as spatial choice processes. Spatial choice analysis can be used to discover the distribution of people's behaviors in space and time. Two adjusted spatial choice models that include models of decision making processes are presented. The comparison results show that adjusted spatial choice models provide efficient and accurate predictions of future crime patterns and can be used as the basis for a law enforcement decision support system. This paper also extends spatial choice modeling to include the class of problems where the decision makers' preferences are derived indirectly through incident reports rather than directly through survey instruments.