Users Constraints in Itemset Mining

TL;DR

This paper introduces a flexible constraint programming model for itemset mining that accommodates user constraints on both items and dataset segments, enhancing query expressiveness and practical applicability.

Contribution

It proposes a general constraint programming framework capable of handling diverse user constraints on items and datasets in itemset mining.

Findings

The model can express complex user constraints.

It efficiently handles queries on specific dataset parts.

Applicable to various data mining scenarios.

Abstract

Discovering significant itemsets is one of the fundamental problems in data mining. It has recently been shown that constraint programming is a flexible way to tackle data mining tasks. With a constraint programming approach, we can easily express and efficiently answer queries with users constraints on items. However, in many practical cases it is possible that queries also express users constraints on the dataset itself. For instance, asking for a particular itemset in a particular part of the dataset. This paper presents a general constraint programming model able to handle any kind of query on the items or the dataset for itemset mining.