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Conference Papers Year : 2017

Data Driven Concept Refinement to Support Avionics Maintenance

Abstract

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.
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Dates and versions

hal-01632675 , version 1 (10-11-2017)

Identifiers

  • HAL Id : hal-01632675 , version 1

Cite

Luis Palacios Medinacelli, Yue Ma, Gaëlle Lortal, Claire Laudy, Chantal Reynaud, et al.. Data Driven Concept Refinement to Support Avionics Maintenance. Proceedings of the IJCAI Workshop on Semantic Machine Learning , Aug 2017, Melbourne, Australia. ⟨hal-01632675⟩
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