From links to meaning: a burglary data case study

Authors:
Giles Oatley;John Zeleznikow;Richard Leary;Brian Ewart
Affiliations:
School of Computing and Technology, University of Sunderland, Sunderland, UK;School of Information Systems, Victoria University, Victoria, Australia;Department of Statistical Science, University College London, London, UK;Division of Psychology, University of Sunderland, Sunderland, UK
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV
Year:
2005

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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.