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Enterprise Knowledge Modeling, UML vs Ontology: Formal Evaluation

Abstract : Everyday activities in enterprises rely heavily on the experts' know-how. Due to experts departure, the loss of expertise and knowledge is a reoccurring problem in these enterprises. Recently, in order to capture experts knowledge into intelligent systems, formal knowledge representation methods, such as ontologies, are being studied and have caught up with non-formal or semi-formal representation, such as UML. The similarities and differences between UML class diagram and computational ontology have for long raised questions about the possibility of synthesizing them in a common representation (usually an ontology). Indeed, the problem of migrating knowledge encoded in UML into an ontology is an active research domain. This paper outlines our approach, which is based on semantic matching between existing ontologies and a UML class diagram, to support UML driven ontology refactoring and engineering.
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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-02753707
Contributeur : Ciad - Université de Bourgogne <>
Soumis le : mercredi 3 juin 2020 - 19:50:17
Dernière modification le : vendredi 5 juin 2020 - 03:44:50

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Meriem Mejhed Mkhinini, Ouassila Labbani, Christophe Nicolle. Enterprise Knowledge Modeling, UML vs Ontology: Formal Evaluation. 2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP), IEEE, Sep 2019, Cluj-Napoca, Romania. pp.127-134, ⟨10.1109/ICCP48234.2019.8959686⟩. ⟨hal-02753707⟩

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