FCA-Based Concept Detection in a RosettaNet PIP Ontology

Jamel Eddine Jridi, Guy Lapalme

Abstract: This paper presents an FCA-based methodology for concept detection in a flat ontology. We apply this approach to an automatically generated ontology for a RosettaNet Partner Interface Process (PIP) which does not take advantage of some important OWL semantic relations like subClassOf. The goal of our approach is to regroup ontology classes sharing a set of properties (Data and Object Property) in order to improve the quality, readability and the inheritance richness of a flat ontology.