A guided walk into link key candidate extraction with relational concept analysis

Manuel Atencia (1) , Jérôme David (1) , Jérôme Euzenat (1) , Amedeo Napoli (2) , Jérémy Vizzini (1)

1 MOEX - Evolution de la connaissance
2 ORPAILLEUR - Knowledge representation, reasonning

Data interlinking is an important task for linked data interoperability. One of the possible techniques for finding links is the use of link keys which generalise relational keys to pairs of RDF models. We show how link key candidates may be directly extracted from RDF data sets by encoding the extraction problem in relational concept analysis. This method deals with non functional properties and circular dependent link key expressions. As such, it generalises those presented for non dependent link keys and link keys over the relational model. The proposed method is able to return link key candidates involving several classes at once.

Mots clés: Formal Concept Analysis; Relational Concept Analysis; Linked data; Link key; Data interlinking; Resource Description Framework

Domaines: Intelligence artificielle [cs.AI]; Web

Manuel Atencia, Jérôme David, Jérôme Euzenat, Amedeo Napoli, Jérémy Vizzini. A guided walk into link key candidate extraction with relational concept analysis. ISWC 2019 - 18th International Semantic Web Conference, Oct 2019, Auckland, New Zealand. pp.1-9. ⟨hal-02984963⟩