We describe here a general approach for rare itemset mining. While mining literature has
been almost exclusively focused on frequent itemsets, in many practical situations rare ones …

In some situations, finding the rare association rule is of higher importance than the frequent
itemset. Unique rules represent rare cases, activities, or events in real-world applications. It …

The aim of this paper is to model and mine patterns combining several local patterns (n-ary
patterns). First, the user expresses his/her query under constraints involving n-ary patterns …

Previously, exception rules have been defined as association rules with low support and
high confidence. Exception rules are important in data mining, as they form rules that can be …

On account of the enormous amounts of rules that can be produced by data mining
algorithms, knowledge post-processing is a difficult stage in an association rule discovery …

This article presents an algorithm that seeks every possible exception rule that violates a
commonsense rule and satisfies several assumptions of simplicity. Exception rules, which …

A formal framework for data mining with association rules is introduced. The framework is
based on a logical calculus of association rules which is enhanced by several formal tools …

Subgroup discovery is a broadly applicable data mining technique whose main objective is
the search for descriptions of subgroups of data that are statistically unusual with respect to …

Interesting pattern discovery is an important topic in data mining research. Many different
definitions have been proposed to describe whether a pattern is interesting. Among these …

We propose a method which visualizes irregular multidimensional time-series data as a
sequence of probabilistic prototypes for detecting exceptions from medical test data …