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Stoffel, Kilian
Résultat de la recherche
Swiss health metadata repository : implementation recommendations - requirements, recommended architecture and prototype implementation
2021-6-1, Cotofrei, Paul, De Santo, Alessio, Maalouf, Eliane, Stoffel, Kilian
In the context of a decentralized approach for health data resources, a central metadata repository becomes essential for the identification/description of the necessary resources. A Swiss Health Metadata Repository is expected to enable multiple advantages, namely: to provide a single entry point for searching/retrieving health-related resources; to help identify possible semantic linking between data sources; to provide a consistent data catalog ensured by the use of standardized vocabularies/ontologies; to enable potential exchange of experience and know-how between health data-related projects in Switzerland; and to increase the capacity of research groups to share/access/analyse health related data. This policy brief focuses on the implementation aspects of a proof-of-concept proto-type for Swiss Health Metadata Repository.
A Parallel Approach for Decision Trees Learning from Big Data Streams
2015-6-24, Calistru, Tudor, Cotofrei, Paul, Stoffel, Kilian
Crime Linkage: a Fuzzy MCDM Approach
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.
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.
Design principles of a central metadata repository as a key element of an integrated health information system
2020-1-31, Cotofrei, Paul, Maalouf, Eliane, De Santo, Alessio, Stoffel, Kilian
The Swiss Health System is a complex system with different groups of actors for which data is collected and analyzed using various methods, leading to a large heterogeneity and dispersion of available data. The specificities of a Swiss Health System favor a hybrid infrastructure to manage the heterogeneity and dispersion of Swiss health-related data. This policy brief shows the importance of a metadata management infrastructure to identify and describe health data resources and highlights several essential key elements for the design of a metadata repository and also raises important practical questions.
The CriLiM Methodology: Crime Linkage with a Fuzzy MCDM Approach
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.
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.
Personalized view of Swiss Public Health Statistical Data
2018, De Santo, Alessio, Cotofrei, Paul, Stoffel, Kilian
A Clustering Topology forWireless Sensor Networks: New Semantics over Network Topology
2013-7-29, Calistru, Tudor, Cotofrei, Paul, Stoffel, Kilian
Temporal Rules over Time Structures with Different Granularities - a Stochastic Approach
2011, Cotofrei, Paul, Stoffel, Kilian