Pattern Detection in Forensic Case Data Using Graph Theory: Application to Heroin Cutting Agents
Détails
Etat: Public
Version: de l'auteur⸱e
ID Serval
serval:BIB_B4252E224FE7
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Pattern Detection in Forensic Case Data Using Graph Theory: Application to Heroin Cutting Agents
Périodique
Forensic Science International
Statut éditorial
Publié
Date de publication
2006
Résumé
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.
Mots-clé
Heroin seizures, Profiling, Adjacency matrix, Co-occurrences, Swiss cantons
Création de la notice
21/01/2008 11:01
Dernière modification de la notice
20/08/2019 16:22
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