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Combined Detection Model for Criminal Network Detection

  • Fatih Ozgul
  • Zeki Erdem
  • Chris Bowerman
  • Julian Bondy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6122)

Abstract

Detecting criminal networks from arrest data and offender demographics data made possible with our previous models such as GDM, OGDM, and SoDM and each of them proved successful on different types of criminal networks. To benefit from all features of police arrest data and offender demographics, a new combined model is developed and called as combined detection model (ComDM). ComDM uses crime location, date and modus operandi similarity as well as surname and hometown similarity to detect criminal networks in crime data. ComDM is tested on two datasets and performed better than other models.

Keywords

Criminal networks crime data mining clustering group detection police arrest data offender demographics 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Fatih Ozgul
    • 1
  • Zeki Erdem
    • 2
  • Chris Bowerman
    • 1
  • Julian Bondy
    • 3
  1. 1.Faculty of Computing, Engineering &TechnologyUniversity of SunderlandSunderlandUnited Kingdom
  2. 2.TUBITAK- UEKAEInformation Technologies InstituteGebzeTurkey
  3. 3.School of Global Studies, Social Science & PlanningRMIT UniversityMelbourneAustralia

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