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  4. The CriLiM Methodology: Crime Linkage with a Fuzzy MCDM Approach
 
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The CriLiM Methodology: Crime Linkage with a Fuzzy MCDM Approach

Auteur(s)
Albertetti, Fabrizio 
Institut du management de l'information 
Cotofrei, Paul 
Institut du management de l'information 
Grossrieder, Lionel
Ribaux, Olivier
Stoffel, Kilian 
Institut du management de l'information 
Maison d'édition
: IEEE
Date de parution
2013-8-12
De la page
67
A la page
74
Mots-clés
  • Crime analysis
  • crime linkage
  • fuzzy MCDM
  • Crime analysis

  • crime linkage

  • fuzzy MCDM

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.
Notes
, 2013
Nom de l'événement
European Intelligence and Security Informatics (EISIC)
Lieu
Uppsala, Sweden
Lié au projet
An Intelligent Process-driven Knowledge Extraction Framework for Crime Analysis 
Identifiants
https://libra.unine.ch/handle/123456789/18914
Type de publication
conference paper
Dossier(s) à télécharger
 main article: 2013-12-19_1135_2179.pdf (388.37 KB)
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