DocumentCode :
2054471
Title :
Finding Criminal Attractors Based on Offenders´ Directionality of Crimes
Author :
Frank, Richard ; Andresen, Martin A. ; Cheng, Connie ; Brantingham, Patricia
Author_Institution :
Sch. of Criminology, Simon Fraser Univ., Burnaby, BC, Canada
fYear :
2011
fDate :
12-14 Sept. 2011
Firstpage :
86
Lastpage :
93
Abstract :
According to Crime Pattern Theory, individuals all have routine daily activities which require frequent travel between several nodes, with each being used for a different purpose, such as home, work or shopping. As people move between these nodes, their familiarity with the spatial area around the nodes, as well as between nodes, increases. Offenders have the same spatial movement patterns and Awareness Spaces as regular people, hence according to theory an offender will commit the crimes in their own Awareness Space. This idea is used to predict the location of the nodes within the Awareness Space of offenders. The activities of 57,962 offenders who were charged or charges were recommended against them were used to test this idea by mapping their offense locations with respect to their home locations to determine the directions they move. Once directionality to crime was established for each offender, a unique clustering technique, based on K-Means, was used to calculate their Cardinal Directions through which the awareness nodes for all offenders were calculated. It was found that, by looking at the results of various clustering parameters, offenders tend to move towards central shopping areas in a city, and commit crimes along the way. Almost all cluster centers were within one kilometer of a shopping center. This technique of finding Criminal Attractors allows for the reconstruction of the spatial profile of offenders, which allows for narrowing the possible suspects for new crimes.
Keywords :
criminal law; pattern clustering; police data processing; K-means clustering; awareness space; cardinal direction; crime directionality; crime pattern theory; criminal attractor; offender profile; spatial movement pattern; Cities and towns; Data models; Databases; Educational institutions; Mathematical model; Space exploration; Visualization; clustering; criminal attractor; directionality; offender profile;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligence and Security Informatics Conference (EISIC), 2011 European
Conference_Location :
Athens
Print_ISBN :
978-1-4577-1464-1
Electronic_ISBN :
978-0-7695-4406-9
Type :
conf
DOI :
10.1109/EISIC.2011.34
Filename :
6061219
Link To Document :
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