Graph-FCA in Practice

Abstract : 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.
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International Conference on Conceptual Structures (ICCS), Jul 2016, Annecy, France. pp.107 - 121, 2016, LNAI 9717. 〈10.1007/978-3-319-40985-6_9〉
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Sébastien Ferré, Peggy Cellier. Graph-FCA in Practice. International Conference on Conceptual Structures (ICCS), Jul 2016, Annecy, France. pp.107 - 121, 2016, LNAI 9717. 〈10.1007/978-3-319-40985-6_9〉. 〈hal-01405491〉

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