Using Grammar-Based Genetic Programming for Mining Subsumption Axioms Involving Complex Class Expressions

Rémi Felin (1, 2, 3) , Andrea G. B. Tettamanzi (1)

1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
2 UniCA - Université Côte d'Azur
3 I3S - Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis

Ontology enrichment is a key task in the area of the Semantic Web. It allows directly to enrich the links between entities of the semantic Web and thus adding information. Our research area is part of this objective with the search for axioms using an evolutionary process. We propose an adaptation resulting from the coupling between evolutionary algorithms and the theory of possibilities in order to allow the research of axioms of subsumption composed of complex classes.

Mots clés: Ontology Learning; OWL 2 Axiom; Subsumption Axioms; Grammatical Evolution

Domaines: Intelligence artificielle [cs.AI]; Base de données [cs.DB]; Recherche d'information [cs.IR]

Rémi Felin, Andrea G. B. Tettamanzi. Using Grammar-Based Genetic Programming for Mining Subsumption Axioms Involving Complex Class Expressions. WI-IAT 2021 - 20th IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Dec 2021, Melbourne, Australia. ⟨10.1145/3486622.3494025⟩. ⟨hal-03519365⟩