title: Pattern detection in forensic case data using graph theory: application to heroin cutting agents.
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 co-occurrences to establish several main combinations has been done. Results illustrate the practical potential of mathematical models in forensic data analysis.
authors.affiliation: Institut de Police Scientifique et de Criminologie, Ecole des Sciences Criminelles, Université de Lausanne, Batochime, CH-1015, Switzerland.
authors.forename: Anne-Laure
authors.initials: AL
authors.lastname: Terrettaz-Zufferey
authors.forename: Frédéric
authors.initials: F
authors.lastname: Ratle
authors.forename: Olivier
authors.initials: O
authors.lastname: Ribaux
authors.forename: Pierre
authors.initials: P
authors.lastname: Esseiva
authors.forename: Mikhail
authors.initials: M
authors.lastname: Kanevski