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Mining for offender group detection and story of a police operation
Ozgul, F., Bondy, J. and Aksoy, H.
Since discovery of an underlying organisational structure
from crime data leads the investigation to terrorist cells or
organised crime groups, detecting covert networks are
important to crime investigation. As shown in application
of Offender Group Detection Model (OGDM), which is
developed and tested on a theft network in Bursa, Turkey,
use of effective data mining methods can reveal offender
groups. OGDM detected seven ruling members of twenty
network members. Based on initial findings of OGDM;
thirty-four offenders are considered to be in a single
offender group where seven of them were ruling
members. After Operation Cash was launched, the police
arrested the seven detected ruling members, and
confirmed that the real crime network was consisting of
20 members of which 3 whom had never been previously
identified or arrested. The police arrested 17 people,
recovered worth US$200,000 of stolen goods, and cash
worth US$180,000. |
Cite as: Ozgul, F., Bondy, J. and Aksoy, H. (2007). Mining for offender group detection and story of a police operation. In Proc. Sixth Australasian Data Mining Conference (AusDM 2007), Gold Coast, Australia. CRPIT, 70. Christen, P., Kennedy, P. J., Li, J., Kolyshkina, I. and Williams, G. J., Eds. ACS. 189-193. |
(from crpit.com)
(local if available)
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