Attribute Classification and Reduct Computation in Multi-Adjoint Concept Lattices

The problem of reducing information in databases is an important topic in formal concept analysis, which has been studied in several articles. In this article, we consider the fuzzy environment of the multi-adjoint concept lattices, since it is a general fuzzy framework that allows us to easily establish degrees of preference on the elements of the considered database. We introduce algorithms to discover the information contained in the relational system. By means of these algorithms, we classify the attributes of a multi-adjoint context, and build a minimal subset of attributes preserving the information of the original knowledge system.

Automated summary

The article discusses the issue of reducing information in databases through formal concept analysis, focusing on multi-adjoint concept lattices in a fuzzy environment. Algorithms are introduced to discover information in relational systems, allowing for classification and creation of minimal attribute subsets that preserve the original knowledge system's information.