Decision implication is a basic form of knowledge representation of formal concept analysis
in the setting of decision-making. Concept rules are decision implications that reveal the …

Abstract Concept lattices are widely used as a knowledge structure in many real-life
applications and the updating of a formal context is inevitable in most cases. How to …

Decision-making is important in all science-based professions, where specialists apply their
knowledge to making valuable decisions. In Formal Concept Analysis, decision-making …

Decision implication is an elementary representation of decision knowledge in formal
concept analysis. Decision implication canonical basis (DICB), a set of decision implications …

Fuzzy decision implication (FDI) is regarded as a basic form of knowledge representation in
fuzzy decision based formal concept analysis. How to reduce redundant FDIs and generate …

Formal concept analysis is able to visualize and represent knowledge using concept lattice
and (attribute) implication. Decision implication is a counterpart of implication in the setting …

As an important tool for data analysis and knowledge processing, formal concept analysis
has been applied to many fields. In this paper, we introduce a decomposition method of a …

Abstract Formal Concept Analysis (FCA) is a method rooted in order theory, with the aim of
analyzing and visually representing concepts. Decision implication serves as a fundamental …

Concept lattice reduction is an important task related to formal concept analysis (FCA), a
technique for knowledge extraction from binary relational data. Concept lattice reduction …

Formal concept analysis is a powerful tool in analyzing data and extracting rules from the
formal context. The main framework of formal concept analysis is concept lattice which …