Our central aim is the development of decision support systems based on appropriate technology for such purposes 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, with examples taken from the authors’ own work a United Kingdom police force.

Discussion and experimentation include exploratory techniques from spatial statistics and forensic psychology. The crime matching techniques used are case-based reasoning, logic programming and ontologies, and naïve Bayes augmented with spatio-temporal features. The crime prediction techniques are survival analysis and Bayesian networks.


Bayesian Network Geographical Information System Logic Programming Bayesian Belief Network Forensic Psychology 
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 London Limited 2005

Authors and Affiliations

  • G. C. Oatley
    • 1
  • J. Zeleznikow
    • 2
  • B. W. Ewart
    • 3
  1. 1.School of Computing and TechnologyUniversity of SunderlandUK
  2. 2.School of Information SystemsVictoria UniversityAustralia
  3. 3.Division of PsychologyUniversity of SunderlandUK

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