Three-way concept analysis (3WCA) is a framework based on Formal concept analysis and
three-way decisions is used in the field of knowledge discovery to solve uncertainties in …

Formal concept analysis (FCA) is a tool for extracting natural clusters from objects and
attributes represented as a binary table. Several parallel and distributed algorithms have …

Three-way concept analysis (3WCA), a combination of three-way decision and formal
concept analysis, is widely used in the field of knowledge discovery. Generally, constructing …

In the process of knowledge discovery and representation in large datasets using formal
concept analysis, complexity plays a major role in identifying the formal concepts and …

In recent years, the increasing complexity of real problems has directed the attention of
many types of research, especially those handling large datasets. Formal concept analysis …

Formal concept analysis (FCA) is a powerful tool for data mining, ontology research, web
semantic retrieval, software engineering, and knowledge discovery. Concept lattice is the …

Abstract Introduced by Rudolf Wille in the mid-80s, Formal Concept Analysis (FCA) is a
mathematical framework that offers conceptual data analysis and knowledge discovery. FCA …

In the basic setting of formal concept analysis, a many-valued attribute needs to be replaced
with several one-valued attributes. These one-valued attributes can be interpreted as a …

Formal Concept Analysis (FCA) is interested in the formation of concept lattices from binary
relations between objects and attributes, aka contexts. Many algorithms have been …

Abstract The theory of Formal Concept Analysis (FCA) finds diverse applications in fields like
knowledge extraction, cognitive concept learning and data mining. The construction of a …