Data Driven Concept Refinement to Support Avionics Maintenance
| Autor: | Palacios Medinacelli, Luis, Ma, Yue, Lortal, Gaëlle, Laudy, Claire, Reynaud, Chantal, Palacios, Luis |
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| Přispěvatelé: | Données et Connaissances Massives et Hétérogènes (LRI) (LaHDAK - LRI), Laboratoire de Recherche en Informatique (LRI), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Thales Research and Technology [Palaiseau], THALES |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | Proceedings of the IJCAI Workshop on Semantic Machine Learning Proceedings of the IJCAI Workshop on Semantic Machine Learning, Aug 2017, Melbourne, Australia |
| Popis: | International audience; Description Logic Ontologies are one of the most important knowledge representation formalisms nowadays which, broadly speaking, consist of classes of objects and their relations. Given a set of objects as samples and a class expression describing them, we present ongoing work that formalizes which properties of these objects are the most relevant for the given class expression to capture them. Moreover , we provide guidance on how to refine the given expression to better describe the set of objects. The approach is used to characterize test results that lead to a specific maintenance corrective action, and in this paper is illustrated to define sub-classes of aviation reports related to specific aircraft equipment. |
| Databáze: | OpenAIRE |
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