The CriLiM Methodology: Crime Linkage with a Fuzzy MCDM Approach

Détails

ID Serval
serval:BIB_DDC129E860AF
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Institution
Titre
The CriLiM Methodology: Crime Linkage with a Fuzzy MCDM Approach
Titre de la conférence
2013 European Intelligence and Security Informatics Conference (EISIC)
Auteur⸱e⸱s
Albertetti  F., Cotofrei  P., Grossrieder  L., Ribaux  O., Stoffel  K.
Editeur
IEEE
Statut éditorial
Publié
Date de publication
2013
Langue
anglais
Résumé
Grouping events having similarities has always been interesting for analysts. Actually, when a label is put on top of a set of events to denote they share common properties, the automation and the capability to conduct reasoning with this set drastically increase. This is particularly true when considering criminal events for crime analysts, conjunction, interpretation and explanation can be key success factors to apprehend criminals. In this paper, we present the CriLiM methodology for investigating both serious and high-volume crime. Our artifact consists in implementing a tailored computerized crime linkage system, based on a fuzzy MCDM approach in order to combine spatio-temporal, behavioral, and forensic information. As a proof of concept, series in burglaries are examined from real data and compared to expert results.
Mots-clé
Crime analysis, crime linkage, fuzzy MCDM
Création de la notice
15/04/2016 17:24
Dernière modification de la notice
21/08/2019 5:15
Données d'usage