The CriLiM Methodology: Crime Linkage with a Fuzzy MCDM Approach

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.

, 2013