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Modelling crime linkage with Bayesian networks.

作者信息

de Zoete Jacob, Sjerps Marjan, Lagnado David, Fenton Norman

机构信息

University of Amsterdam, The Netherlands.

Netherlands Forensic Institute, The Netherlands.

出版信息

Sci Justice. 2015 May;55(3):209-17. doi: 10.1016/j.scijus.2014.11.005. Epub 2014 Dec 19.

DOI:10.1016/j.scijus.2014.11.005
PMID:25934374
Abstract

When two or more crimes show specific similarities, such as a very distinct modus operandi, the probability that they were committed by the same offender becomes of interest. This probability depends on the degree of similarity and distinctiveness. We show how Bayesian networks can be used to model different evidential structures that can occur when linking crimes, and how they assist in understanding the complex underlying dependencies. That is, how evidence that is obtained in one case can be used in another and vice versa. The flip side of this is that the intuitive decision to "unlink" a case in which exculpatory evidence is obtained leads to serious overestimation of the strength of the remaining cases.

摘要

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