Mining for offender group detection and story of a police operation

Bondy, J and Aksoy, H 2007, 'Mining for offender group detection and story of a police operation', CRIPT (Conferences in Research and Practice in Information Technology), vol. 70, pp. 185-190.


Document type: Journal Article
Collection: Journal Articles

Title Mining for offender group detection and story of a police operation
Author(s) Bondy, J
Aksoy, H
Year 2007
Journal name CRIPT (Conferences in Research and Practice in Information Technology)
Volume number 70
Start page 185
End page 190
Total pages 6
Publisher Australian Computer Society
Abstract 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 U.S. $ 200,000 of stolen goods, and cash worth U.S. $ 180,000.
Subject Ordinary Differential Equations, Difference Equations and Dynamical Systems
Police Administration, Procedures and Practice
Keyword(s) crime data mining
group detection
social network analysis
Copyright notice Copyright © 2007, Australian Computer Society, Inc.
ISSN 1445-1336
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