Linkex: A Tool for Link Key Discovery Based on Pattern Structures

Nacira Abbas (1) , Jérôme David (2) , Amedeo Napoli (1)

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

Links constitute the core of Linked Data philosophy. With the high growth of data published in the web, many frameworks have been proposed to deal with the link discovery problem, and particularly the identity links. Finding such kinds of links between different RDF data sets is a critical task. In this position paper, we focus on link key which consists of sets of pairs of properties identifying the same entities across heterogeneous datasets. We also propose to formalize the problem of link key discovery using Pattern Structures (PS), the generalization of Formal Concept Analysis dealing with non binary datasets. After providing the proper definitions of link keys and setting the problem in terms of PS, we show that the intents of the pattern concepts correspond to link keys and their extents to sets of identity links generated by their intents. Finally, we discuss an implementation of this framework and we show the applicability and the scalability of the proposed method.

Mots clés: RDF; Linked Data; Pattern Structures; Link key

Domaines: Intelligence artificielle [cs.AI]

Nacira Abbas, Jérôme David, Amedeo Napoli. Linkex: A Tool for Link Key Discovery Based on Pattern Structures. ICFCA 2019 - workshop on Applications and tools of formal concept analysis, Jun 2019, Frankfurt, Germany. pp.33-38. ⟨hal-02168775⟩