Formal concept analysis is about extracting the relationships and hierarchies available from the common attributes shared by objects.
A formal context is, simply, a dyadic Chu space. More precisely:
A (dyadic or two valued) Chu space is a triple , where is a set of objects, and is a set of attributes. The satisfaction relation is a subset of .
The terminology is that used in Formal Concept Analysis. Such an object gives an array representing a relation between a set of objects and a set of attibutes. If an object, , satisfies attribute , that is , one puts a 1 in the - position in the array, otherwise one puts a 0. This is thus the usual classical representation of the relation as a subset of the product. (We will restrict attention to this simple 2-valued case. One can replace but other suitably structured sets, to obtain probabilistic or fuzzy versions of a Formal Context.
The task of the analysis is to see if the data encoded in the array allows one to group objects or attributes together so as to glean more information about the given relationship between the two sets.
To quote from Zhang and Shen:
The novel idea of FCA is the clustering of attributes based on the algebraic principle of Galois connection, forming a partially ordered set called (a) concept lattice. The clustering determines which collection of attributes forms a coherent entity called a concept, by the philosophical criteria of unity between extension and intension. The extension of a concept consists of all objects belonging to the concept, while the intension of a concept consists of attributes common to all these objects. One can then take this as the defining property of a concept: a collection of attributes which agrees with the intension of its extension.
Given a Formal Context, , we define two mappings:
and
The formal context / Chu space is said to be extensional if is injective and is said to be separable if is injective.
The two mappings and extend to give mappings and , defined by
and
Ganter, B., & Wille, R. Formal concept analysis: mathematical foundations. Springer Science & Business Media, (2012). doi
Radim Belohlavek, Introduction to formal concept analysis pdf
Café discussion Formal Concept Analysis
Guo-Qiang Zhang, Shen, G.: Approximable Concepts, Chu spaces, and information systems, Theory and Applications of Categories 17, 2006, no.7
Last revised on December 9, 2021 at 11:48:27. See the history of this page for a list of all contributions to it.