=Paper=
{{Paper
|id=Vol-1624/inv2
|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-1624/inv2.pdf
|volume=Vol-1624
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==None==
<pdf width="1500px">https://ceur-ws.org/Vol-1624/inv2.pdf</pdf>
<pre>
Data Interlinking with Formal Concept Analysis
                 and Link Keys

                                    Jérôme Euzenat

                   INRIA & Univ. Grenoble Alpes, Grenoble, France



        Abstract. Data interlinking, the problem of linking pairs of nodes in
        RDF graphs corresponding to the same resource, is an important task
        for linked open data. We introduced the notion of link keys as a way
        to identify such node pairs [1]. Link keys generalise in several ways keys
        in relational algebra. Thus, we consider how they could be extracted
        from data with Formal Concept Analysis. We show that an appropriate
        encoding makes the notion of candidate link keys correspond to formal
        concepts [2]. However candidate link keys are not yet link keys as they
        need to be selected through appropriate measures. We discuss how the
        measurement and concept extraction processes may be interleaved. If
        time permits we will also discuss extensions of this model to residual
        link keys and mutually dependent link keys1 .

        Keywords: Linked Data, Formal Concept Analysis


References
1. Atencia, M., David, J., Euzenat, J.: Data interlinking through robust linkkey extrac-
   tion. In: Proc. 21st European Conference on Artificial Intelligence (ECAI), Praha
   (CZ). (2014) 15–20
2. Atencia, M., David, J., Euzenat, J.: What can FCA do for database linkkey extrac-
   tion? In: Proc. 3rd ECAI workshop on What can FCA do for Artificial Intelligence?
   (FCA4AI), Praha (CZ). (2014) 85–92




1
    This work has been developed in collaboration with Manuel Atencia, Jérôme David
    and Amedeo Napoli.

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