Graph-FCA in Practice

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9717)


With the rise of the Semantic Web, more and more relational data are made available in the form of knowledge graphs (e.g., RDF, conceptual graphs). A challenge is to discover conceptual structures in those graphs, in the same way as Formal Concept Analysis (FCA) discovers conceptual structures in tables. Graph-FCA has been introduced in a previous work as an extension of FCA for such knowledge graphs. In this paper, algorithmic aspects and use cases are explored in order to study the feasibility and usefulness of G-FCA. We consider two use cases. The first one extracts linguistic structures from parse trees, comparing two graph models. The second one extracts workflow patterns from cooking recipes, highlighting the benefits of n-ary relationships and concepts.


Formal Concept Analysis Knowledge graph Semantic Web Graph pattern 


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© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.IRISA/Université de Rennes 1Rennes CedexFrance
  2. 2.IRISA/INSA RennesRennes CedexFrance

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