In this chapter, we introduce Formal Concept Analysis (FCA) and some of its extensions.
FCA is a formalism based on lattice theory aimed at data analysis and knowledge …

Subgroup discovery (SD) is an exploratory pattern mining paradigm that comes into its own
when dealing with large real-world data, which typically involves many attributes, of a …

We introduce the problem of robust subgroup discovery, ie, finding a set of interpretable
descriptions of subsets that 1) stand out with respect to one or more target attributes, 2) are …

In the era of big data, SQL databases face significant challenges in handling vast volumes of
data efficiently. This article explores optimization techniques and best practices for …

Subgroup discovery (SD) is the task of discovering interpretable patterns in the data that
stand out wrt some property of interest. Discovering patterns that accurately discriminate a …

Sorption-enhanced reverse water–gas shift (SE-RWGS, here designated as 'COMAX') was
studied with bifunctional reactive sorbents. First proof-of-concept is presented of the …

In recent years, the field of pattern mining has shifted to user-centered methods. In such a
context, it is necessary to have a tight coupling between the system and the user where …

This paper considers the capacity expansion problem in two-sided matchings, where the
policymaker is allowed to allocate some extra seats as well as the standard seats. In medical …

Subgroup discovery is the task of discovering patterns that accurately discriminate a class
label from the others. Existing approaches can uncover such patterns either through an …

In recent years, pattern mining has moved from a slow-moving repeated three-step process
to a much more agile iterative/user-centric mining model. A vital ingredient of this framework …