Non-monotonic Extensions to Formal Concept Analysis via Object Preferences
Lucas Carr, Nicholas Leisegang, Thomas Meyer, Sebastian Rudolph

TL;DR
This paper extends Formal Concept Analysis by introducing a non-monotonic conditional based on object preferences, aligning FCA with non-monotonic reasoning and enabling a more flexible, exception-tolerant concept hierarchy.
Contribution
It introduces a non-monotonic conditional in FCA that adheres to KLM postulates and characterizes typical concepts as a meet semi-lattice within the concept lattice.
Findings
Non-monotonic consequence relation consistent with KLM postulates.
Typical concepts form a meet semi-lattice of the original concept lattice.
Foundation for algebraic structures of prototypical concepts.
Abstract
Formal Concept Analysis (FCA) is an approach to creating a conceptual hierarchy in which a \textit{concept lattice} is generated from a \textit{formal context}. That is, a triple consisting of a set of objects, , a set of attributes, , and an incidence relation on . A \textit{concept} is then modelled as a pair consisting of a set of objects (the \textit{extent}), and a set of shared attributes (the \textit{intent}). Implications in FCA describe how one set of attributes follows from another. The semantics of these implications closely resemble that of logical consequence in classical logic. In that sense, it describes a monotonic conditional. The contributions of this paper are two-fold. First, we introduce a non-monotonic conditional between sets of attributes, which assumes a preference over the set of objects. We show that this conditional gives rise to a…
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Taxonomy
TopicsRough Sets and Fuzzy Logic
MethodsSparse Evolutionary Training
