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.
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Oatley, G., Zeleznikow, J., Leary, R., Ewart, B. (2005). From Links to Meaning: A Burglary Data Case Study. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3684. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11554028_114
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DOI: https://doi.org/10.1007/11554028_114
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28897-8
Online ISBN: 978-3-540-31997-9
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