Rises for Measuring Local Distributivity in Lattices
This provides a tool for data analysts in Formal Concept Analysis to measure distributivity, but it is incremental as it builds on existing lattice theory.
The paper tackles the lack of a standardized measure for distributivity in lattices, particularly in Formal Concept Analysis, by introducing rises as a quantification method, showing that a lattice is distributive if and only if no non-unit rises occur.
Distributivity is a well-established and extensively studied notion in lattice theory. In the context of data analysis, particularly within Formal Concept Analysis (FCA), lattices are often observed to exhibit a high degree of distributivity. However, no standardized measure exists to quantify this property. In this paper, we introduce the notion of rises in (concept) lattices as a means to assess distributivity. Rises capture how the number of attributes or objects in covering concepts change within the concept lattice. We show that a lattice is distributive if and only if no non-unit rises occur. Furthermore, we relate rises to the classical notion of meet- and join distributivity. We observe that concept lattices from real-world data are to a high degree join-distributive, but much less meet-distributive. We additionally study how join-distributivity manifests on the level of ordered sets.