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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
    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
    Selecting optimal split-functions for large datasets
    (Godalming: Springer-Verlag London Ltd, 2001)
    Stoffel, Kilian 
    ;
    Raileanu, Laura Elena
    ;
    Bramer, Max
    ;
    Preece, Alun
    ;
    Coenen, Frans
    Decision tree induction has become one of the most popular methods for classification and prediction. The key step in the process of inferring decision trees is finding the right criteria for splitting the training set into smaller and smaller subsets so that, ideally, all elements of a subset finally belong to one class. These split criteria can be defined in different ways (e.g. minimizing impurity of a subset, or minimizing entropy in a subset), and therefore they emphasize different properties of the inferred tree, such as size or classification accuracy. In this paper we analyze if the split functions introduced in a statistical and machine learning context are also well suited for a KDD context. We selected two well known split functions, namely Gini Index (CART) and Information Gain (C4.5) and introduced our own family of split functions and tested them on 9,000 data sets of different sizes (from 200 to 20, 000 tuples). The tests have shown that the two popular functions are very sensitive to the variation of the training set sizes and therefore the quality of the inferred trees is highly dependent on the training set size. At the same time however, we were able to show that the simplest members of the introduced family of split functions behave in a very predictable way and, furthermore, the created trees were superior to the trees inferred using the Gini Index or the Information Gain based on our evaluation criteria.
  • Publication
    Accès libre
    Watch-dictaphone for Automatic Medical Codification
    (2008)
    Grassi, Sara
    ;
    Heck, P.
    ;
    Stadelmann, Patrick
    ;
    Cotofrei, Paul 
    ;
    Dinissen, P.
    ;
    Meylan, F.
    ;
    Mignot, J.-P.
    ;
    Pfeuti, J.-N.
    ;
    Piccini, F.
    ;
    Geiser, P.
    ;
    Biundo, Giuseppina
    ;
    Farine, Pierre-André
    ;
    Grupp, Joachim
    ;
    Stoffel, Kilian 
    This paper describes the development of a voice data recording watch and the accompanying software and hardware needed to build an integrated solution for medical data capture and auto-matic codification. The developed system is used to capture on the stand-alone watch, either by voice recording or by form-filling, the relevant information on the healthcare service being provided. The captured information is stored locally and then downloaded to a PC, via a USB connection. In the PC, speech is translated first into text and then into medical codification, with minimum user-intervention. The resulting information is stored into local or cen-tralized patient databases, to be sent later to 3rd-party SW for billing, reporting and statistics. The user controls the watch either via a touch-screen based interface or via a voice-driven interface for hands-free operation. Although this work is multidisciplinary, in this paper the emphasis is put on the description of the DSP implementation.
  • Publication
    Métadonnées seulement
    Semantic indexing for complex patient grouping
    (1997)
    Stoffel, Kilian 
    ;
    Saltz, Joel
    ;
    Hendler, James
    ;
    Dick, James
    ;
    Merz, William
    ;
    Miller, Robert
  • Publication
    Métadonnées seulement
    First-Order Logic Based Formalism for Temporal Data Mining
    (Berlin: Springer-Verlag, 2005)
    Cotofrei, Paul 
    ;
    Stoffel, Kilian 
    In this article we define a formalism for a methodology that has as purpose the discovery of knowledge, represented in the form of general Horn clauses, inferred from databases with a temporal dimension. To obtain what we called temporal rules, a discretisation phase that extracts events from raw data is applied first, followed by an induction phase, which constructs classification trees from these events. The theoretical framework we proposed, based on first-order temporal logic, permits us to define the main notions (event, temporal rule, constraint) in a formal way. The concept of consistent linear time structure allows us to introduce the notions of general interpretation and of confidence. These notions open the possibility to use statistical approaches in the design of algorithms for inferring higher order temporal rules, denoted temporal meta-rules.
  • Publication
    Métadonnées seulement
  • Publication
    Métadonnées seulement
  • Publication
    Accès libre
    From Police Reports to Data Marts: a Step Towards a Crime Analysis Framework
    (: Springer, 2012-11-11)
    Albertetti, Fabrizio 
    ;
    Stoffel, Kilian 
    Nowadays, crime analyses are often conducted with computational methods. These methods, using several different systems (such as decision support systems), need to handle forensic data in a specific way. In this paper we present a methodology to structure police report data for crime analysis. The proposed artifact is mainly about applying data warehousing concepts to forensic data in a crime analysis perspective. Moreover, a proof of concept is carried out with real forensic data to illustrate and evaluate our methodology. These experiments highlight the need of such framework for crime analysis.
  • Publication
    Métadonnées seulement
    Ein Prototyp des PACT-Modells
    (Fribourg Université de Fribourg, 1991)
    Stoffel, Kilian 
    ;
    Hirsbrunner, Béat