We introduce MiningZinc, a declarative framework for constraint-based data mining.
MiningZinc consists of two key components: a language component and an execution …

This paper provides an overview of the current state-of-the-art on using constraints in
knowledge discovery and data mining. The use of constraints in a data mining task requires …

Abstract The Within-Cluster Sum of Squares (WCSS) is the most used criterion in cluster
analysis. Optimizing this criterion is proved to be NP-Hard and has been studied by different …

Discovering association rules from transaction databases is one of the most studied data
mining task. Many effective techniques have been proposed over the years. All these …

Recently, several constraint programming (CP)/propositional satisfiability (SAT) based
encodings have been proposed to deal with various data mining problems including itemset …

Many pattern mining systems are designed to solve one specific problem, such as frequent,
closed or maximal frequent itemset mining, efficiently. Even though efficient, their …

Constraint programming (CP) and propositional satisfiability (SAT) based framework for
modeling and solving pattern mining tasks has gained a considerable audience in recent …

In this paper, we introduce a new problem, called Top-k SAT, that consists in enumerating
the Top-k models of a propositional formula. A Top-k model is defined as a model with less …

Several propositional satisfiability (SAT) based encodings have been proposed to deal with
various data mining problems including itemset and sequence mining problems. This …

This article provides a viewpoint on the past and possible future development of data mining
technology. On an introductory level, it provides some historical background to the …