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Matching and predicting crimes
Book chapter

Matching and predicting crimes

G.C. Oatley, J. Zeleznikow and B.W. Ewart
Applications and Innovations in Intelligent Systems XII, pp.19-32
Springer, London
2005
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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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UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#16 Peace, Justice and Strong Institutions

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