With the advent of the Web along with the unprecedented amount of information available in
electronic format, conceptual data analysis is more useful and practical than ever, because …

Incomplete decision contexts are a kind of decision formal contexts in which information
about the relationship between some objects and attributes is not available or is lost …

Three-way concept lattices can supply much more information than classical concept lattices
since they contain the positive information and negative information between objects and …

We introduce the notion of iceberg concept lattices and show their use in knowledge
discovery in databases. Iceberg lattices are a conceptual clustering method, which is well …

During the design of concept lattices, complexity plays a major role in computing all the
concepts from the huge incidence matrix. Hence for reducing the size of the lattice, methods …

In order to allow for the analysis of data sets including numerical attributes, several
generalizations of association rule mining based on fuzzy sets have been proposed in the …

Formal Concept Analysis (FCA), in which data is represented as a formal context, offers a
framework for Association Rules Mining (ARM) by handling functional dependencies in the …

Social bookmarking tools are rapidly emerging on the Web. In such systems users are
setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared …

Abstract Formal Concept Analysis is an unsupervised learning technique for conceptual
clustering. We introduce the notion of iceberg concept lattices and show their use in …

Strong association rules are one of basic types of knowledge. The number of rules is often
huge, which limits their usefulness. Applying concise rule representations with appropriate …