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From Links to Meaning: A Burglary Data Case Study

  • Giles Oatley
  • John Zeleznikow
  • Richard Leary
  • Brian Ewart
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3684)

Abstract

Our central aim is the development of decision support systems for purposes such as profiling single and series of crimes or offenders, and matching and predicting crimes. This paper presents research in this area for the high-volume crime of Burglary Dwelling House, examining the operational use of networks and the metric of brokerage from the social network analysis literature. Our work builds upon several years of experimentation using forensic psychology guided exploratory techniques from artificial intelligence, statistics and spatial statistics.

Keywords

Criminal Activity Forensic Psychology Link Mining Brokerage Network Social Network Analysis Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Giles Oatley
    • 1
  • John Zeleznikow
    • 2
  • Richard Leary
    • 3
  • Brian Ewart
    • 4
  1. 1.School of Computing and TechnologyUniversity of SunderlandSunderlandUK
  2. 2.School of Information SystemsVictoria UniversityAustralia
  3. 3.Department of Statistical ScienceUniversity College LondonLondonUK
  4. 4.Division of PsychologyUniversity of SunderlandSunderlandUK

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