RMIT University
Browse

Combined detection model for criminal network detection

conference contribution
posted on 2024-10-31, 10:33 authored by Fatih Ozgul, Zeki Erdem, Chris Bowerman, Julian Bondy
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.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1007/978-3-642-13601-6_1
  2. 2.
    ISBN - Is published in 9783642136009 (urn:isbn:9783642136009)

Start page

1

End page

14

Total pages

14

Outlet

Intelligence and Security Informatics Pacific Asia Workshop Proceedings Volume 6122

Editors

Hsinchun Chen, Michael Chau, Shu-hsing Li, Shalini Urs, Srinath Srinivasa, G. Alan Wang

Name of conference

PAISI 2010

Publisher

Springer

Start date

2010-06-21

End date

2010-06-21

Language

English

Copyright

© 2010 Springer-Verlag

Former Identifier

2006026038

Esploro creation date

2020-06-22

Fedora creation date

2015-01-15

Usage metrics

    Scholarly Works

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC