Pattern Detection in Forensic Case Data Using Graph Theory: Application to Heroin Cutting Agents
Details
State: Public
Version: author
Serval ID
serval:BIB_B4252E224FE7
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Pattern Detection in Forensic Case Data Using Graph Theory: Application to Heroin Cutting Agents
Journal
Forensic Science International
Publication state
Published
Issued date
2006
Abstract
Pattern recognition techniques can be very useful in forensic sciences to point out to relevant sets
of events and potentially encourage an intelligence-led style of policing. In this study, these techniques have
been applied to categorical data corresponding to cutting agents found in heroin seizures. An application of
graph theoretic methods has been performed in order to highlight the possible relationships between the
location of seizures and co-occurrences of particular heroin cutting agents. An analysis of the cooccurrences
to establish several main combinations has been done. Results illustrate the practical potential
of mathematical models in forensic data analysis.
of events and potentially encourage an intelligence-led style of policing. In this study, these techniques have
been applied to categorical data corresponding to cutting agents found in heroin seizures. An application of
graph theoretic methods has been performed in order to highlight the possible relationships between the
location of seizures and co-occurrences of particular heroin cutting agents. An analysis of the cooccurrences
to establish several main combinations has been done. Results illustrate the practical potential
of mathematical models in forensic data analysis.
Keywords
Heroin seizures, Profiling, Adjacency matrix, Co-occurrences, Swiss cantons
Create date
21/01/2008 11:01
Last modification date
20/08/2019 16:22
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