Abstract
This work is motivated by knowledge discovery in attributed graphs. Our approach consists in extending the methodology of frequent closed pattern mining, as developed in Formal Concept Analysis (FCA), to the case where the objects in which attribute patterns may occur are the vertices of a graph, typically representing a social network. For that purpose we extend the framework of abstract concept lattices, in which the extensional space is a pointed join-subsemilattice of the powerset \(X\) of the object set, by considering as the extensional space a weaker structure called a confluence of \(X\). Confluences were recently investigated as intensional spaces in FCA. In this article we show that when the intensional space is a lattice \(L\) and the extensional space is a confluence \(F\) of \(X\), that leads to a set of closure operators, called local closure operators, whose union form the set of intensions of \(F\). We investigate the structure of the set of (extension,intension) pairs, i.e. the set of local concepts built on \((L,F)\) and related local implications. As an example, we consider the detection of all frequent k-communities in an attributed network.
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Notes
- 1.
In data mining the support set of a pattern is the extension of this pattern in a set of objects
- 2.
In that article, these structures were called confluence’s. We use here a more standard terminology.
- 3.
A pattern is said support-closed whenever specializing the pattern decreases its extension [6].
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Many thanks to Sylvie Borne for her help in drawing the figures.
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Soldano, H. (2015). Extensional Confluences and Local Closure Operators. In: Baixeries, J., Sacarea, C., Ojeda-Aciego, M. (eds) Formal Concept Analysis. ICFCA 2015. Lecture Notes in Computer Science(), vol 9113. Springer, Cham. https://doi.org/10.1007/978-3-319-19545-2_8
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