This paper is a tutorial on Formal Concept Analysis (FCA) and its applications. FCA is an
applied branch of Lattice Theory, a mathematical discipline which enables formalisation of …

This paper presents several definitions of “optimal patterns” in triadic data and results of
experimental comparison of five triclustering algorithms on real-world and synthetic …

Addressing the interpretability problem of NMF on Boolean data, Boolean Matrix
Factorization (BMF) uses Boolean algebra to decompose the input into low-rank Boolean …

Formal concept analysis was first used in collaborative filtering for over one decade. Popular
approaches are based on superconcept-subconcept relationship or boolean matrix …

Reduction theory is an important topic in formal concept analysis, and the research of
reduction theory generally focuses on attribute reduction. Attribute reduction deletes …

We propose the usage of two power indices from cooperative game theory and public
choice theory for ranking attributes of closed sets, namely intents of formal concepts (or …

The bond between L-fuzzy formal contexts can be defined as a (Galois) connection between
L-fuzzy concept lattices of L-fuzzy formal contexts. The selection of appropriate bond from …

During the past few years Boolean matrix factorization (BMF) has become an important
direction in data analysis. The minimum description length principle (MDL) was successfully …

In this work we propose and study an approach for collaborative filtering, which is based on
Boolean matrix factorisation and exploits additional (context) information about users and …

Boolean matrix factorization (BMF) is a popular data analysis method summarizing the input
data by Boolean factors. The Boolean nature ensures an easy interpretation of a particular …