Crime Linkage: a Fuzzy MCDM Approach
Author(s)
Grossrieder, Lionel
Ribaux, Olivier
Publisher
: IEEE
Date issued
June 4, 2013
From page
1
To page
3
Subjects
Crime analysis crime linkage fuzzy MCDM
Abstract
Grouping crimes having similarities has always been
interesting for analysts. Actually, when a set of crimes share
common properties, the capability to conduct reasoning and
the automation with this set drastically increase. Conjunction,
interpretation and explanation based on similarities can be key
success factors to apprehend criminals. In this paper, we present
a computerized method for high-volume crime linkage, based
on a fuzzy MCDM approach in order to combine situational,
behavioral, and forensic information. Experiments are conducted
with series in burglaries from real data and compared to expert
results.
interesting for analysts. Actually, when a set of crimes share
common properties, the capability to conduct reasoning and
the automation with this set drastically increase. Conjunction,
interpretation and explanation based on similarities can be key
success factors to apprehend criminals. In this paper, we present
a computerized method for high-volume crime linkage, based
on a fuzzy MCDM approach in order to combine situational,
behavioral, and forensic information. Experiments are conducted
with series in burglaries from real data and compared to expert
results.
Notes
, 2013
Event name
IEEE Intelligence and Security Informatics (ISI) 2013
Location
Seattle
Later version
http://isiconference2013.org/
Publication type
conference paper
File(s)