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Matching and Predicting Crimes

  • Conference paper
Applications and Innovations in Intelligent Systems XII (SGAI 2004)

Abstract

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.

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Author information

Authors and Affiliations

  1. School of Computing and Technology, University of Sunderland, UK

    Dr. G. C. Oatley

  2. School of Information Systems, Victoria University, Australia

    Prof. J. Zeleznikow

  3. Division of Psychology, University of Sunderland, UK

    Dr. B. W. Ewart

Authors
  1. Dr. G. C. Oatley
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  2. Prof. J. Zeleznikow
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  3. Dr. B. W. Ewart
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Editor information

Editors and Affiliations

  1. Napier University, Edinburgh, EH10 5DT, UK

    Ann Macintosh BSc, CEng

  2. Stratum Management Ltd, UK

    Richard Ellis BSc, MSc

  3. Nottingham Trent University, Nottingham

    Tony Allen

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© 2005 Springer-Verlag London Limited

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Oatley, G.C., Zeleznikow, J., Ewart, B.W. (2005). Matching and Predicting Crimes. In: Macintosh, A., Ellis, R., Allen, T. (eds) Applications and Innovations in Intelligent Systems XII. SGAI 2004. Springer, London. https://doi.org/10.1007/1-84628-103-2_2

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  • DOI: https://doi.org/10.1007/1-84628-103-2_2

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-85233-908-1

  • Online ISBN: 978-1-84628-103-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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