Stepwise functional refoundation of relational concept analysis
J\'er\^ome Euzenat (MOEX)

TL;DR
This paper provides a stepwise, formal analysis of relational concept analysis (RCA), characterizing all acceptable solutions as fixed points within a structured solution space, and clarifies RCA's semantics.
Contribution
It introduces a formal, functional framework for RCA, defining the space of solutions and showing RCA returns the least acceptable solution, with methods to find the greatest one.
Findings
RCA's acceptable solutions form a complete sublattice.
RCA returns the least element of the solution set.
A dual operation can generate the greatest solution.
Abstract
Relational concept analysis (RCA) is an extension of formal concept analysis allowing to deal with several related contexts simultaneously. It has been designed for learning description logic theories from data and used within various applications. A puzzling observation about RCA is that it returns a single family of concept lattices although, when the data feature circular dependencies, other solutions may be considered acceptable. The semantics of RCA, provided in an operational way, does not shed light on this issue. In this report, we define these acceptable solutions as those families of concept lattices which belong to the space determined by the initial contexts (well-formed), cannot scale new attributes (saturated), and refer only to concepts of the family (self-supported). We adopt a functional view on the RCA process by defining the space of well-formed solutions and two…
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Taxonomy
TopicsRough Sets and Fuzzy Logic · Semantic Web and Ontologies · Biomedical Text Mining and Ontologies
