Abstract
Purpose – The purpose of this paper is to identify a workable methodology to prioritise those crime scenes which have the greatest opportunity of a forensic recovery to enable effective Crime Scene Investigator (CSI) resource deployment.Design/methodology/approach – The motivation behind this work stemmed from an abundance of volume crime scenes that required examination and a lack of resources that could be deployed. Within a data mining application environment, two supervised learning algorithms were used to model Northamptonshire Police's forensic data to provide a computer‐based model that could predict the outcome of finding a forensic sample at the currently unattended scene of a crime.Findings – Based on past data, a computer model could be produced to predict the probability of finding useful fingerprints, DNA and/or footwear marks at the scene of a volume crime. In this paper, volume crime means burglary dwelling, burglary in commercial buildings, theft of and theft from motor vehicles. The model...
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