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Stoffel, Kilian

Nom
Stoffel, Kilian
Affiliation principale
Fonction
Professeur ordinaire
Email
Kilian.STOFFEL@unine.ch
Identifiants
https://libra.unine.ch/handle/123456789/593

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  • Publication
    Accès libre
    The CriLiM Methodology: Crime Linkage with a Fuzzy MCDM Approach
    (: IEEE, 2013-8-12)
    Albertetti, Fabrizio 
    ;
    Cotofrei, Paul 
    ;
    Grossrieder, Lionel
    ;
    Ribaux, Olivier
    ;
    Stoffel, Kilian 
    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.
  • Publication
    Accès libre
    Crime Linkage: a Fuzzy MCDM Approach
    (: IEEE, 2013-6-4)
    Albertetti, Fabrizio 
    ;
    Cotofrei, Paul 
    ;
    Grossrieder, Lionel
    ;
    Ribaux, Olivier
    ;
    Stoffel, Kilian 
    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.
  • Publication
    Métadonnées seulement
    Fuzzy Extended BPMN for Modelling Crime Analysis Processes
    (2011-5)
    Cotofrei, Paul 
    ;
    Stoffel, Kilian 
    In the frame of an overall project concerning the development of an intelligent process-driven framework for crime analysis, the modelling phase of crime analysis processes requires formal approaches being able to capture both the vague nature of forensic data and the uncertainties and conjectures characterizing the inference structures of this domain. In this context, a first analysis on the feasibility of a fuzzy embedded BPMN using the extensibility mechanism introduced by BPMN 2.0 specification is considered.
  • Publication
    Métadonnées seulement
    Optimal Scene Interpretation: Semantic Management of 3-D Object from a Point Cloud Scene
    (2009-5)
    Cotofrei, Paul 
    ;
    Kuenzi, Christophe 
    ;
    Stoffel, Kilian 
    This paper presents the main concepts of a project under development concerning the analysis process of a scene containing a large number of objects, represented as unstructured point clouds. To achieve what we called the ―optimal scene interpretation‖ (the shortest scene description satisfying the MDL principle) we follow an approach for managing 3-D objects based on a semantic framework based on ontologies for adding and sharing conceptual knowledge about spatial objects.
  • Publication
    Métadonnées seulement
    Stochastic Processes and Temporal Data Mining
    (2007-8)
    Cotofrei, Paul 
    ;
    Stoffel, Kilian 
    This article tries to give an answer to a fundamental question in temporal data mining: ”Under what conditions a temporal rule extracted from up-to-date temporal data keeps its confidence/support for future data”. A possible solution is given by using, on the one hand, a temporal logic formalism which allows the definition of the main notions (event, temporal rule, support, confidence) in a formal way and, on the other hand, the stochastic limit theory. Under this probabilistic temporal framework, the equivalence between the existence of the support of a temporal rule and the law of large numbers is systematically analysed.
  • Publication
    Métadonnées seulement
  • Publication
    Métadonnées seulement
    Temporal granular logic for temporal data mining
    (: IEEE, 2005-7)
    Cotofrei, Paul 
    ;
    Stoffel, Kilian 
    In this article, a formalism for a specific temporal data mining task (the discovery of rules, inferred from databases of events having a temporal dimension), is defined. The proposed theoretical framework, based on first-order temporal logic, allows the definition of the main notions (event, temporal rule, constraint) in a formal way. This formalism is then extended to include the notion of temporal granularity and a detailed study is made to investigate the formal relationships between semantics for the same event in linear time structures with different granularities.