In this paper, we provide a brief summary of elementary research in rule learning. The two
main research directions are descriptive rule learning, with the goal of discovering …

This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

Biclustering, the simultaneous clustering of rows and columns of a data matrix, has proved
its effectiveness in bioinformatics due to its capacity to produce local instead of global …

A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life
Problems Contrast Data Mining: Concepts, Algorithms, and Applications collects recent …

The discovery of discriminative patterns from high-dimensional data offers the possibility to
learn from informative subspaces and pattern-centric features, paving the way to associative …

We introduce the problem of k-pattern set mining, concerned with finding a set of k related
patterns under constraints. This contrasts to regular pattern mining, where one searches for …

Empathy is a necessary component of human communication. However, it has been largely
ignored in favor of other concepts such as emotion and feeling in Affective computing …

In this article we show that there is a strong connection between decision tree learning and
local pattern mining. This connection allows us to solve the computationally hard problem of …

Abstract Outcomes' prediction in Electronic Health Records (EHR) and specifically in Critical
Care is increasingly attracting more exploration and research. In this study, we used clinical …

The COVID-19 pandemic has generated massive data in the healthcare sector in recent
years, encouraging researchers and scientists to uncover the underlying facts. Mining …