User’s Constraints in Itemset Mining
Discovering significant itemsets is one of the fundamental tasks 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 user’s constraints on itemsets. However, in many practical cases queries also involve user’s constraints on the dataset itself. For instance, in a dataset of purchases, the user may want to know which itemset is frequent and the day at which it is frequent. This paper presents a general constraint programming model able to handle any kind of query on the dataset for itemset mining.
Christian Bessiere was partially supported by the ANR project DEMOGRAPH (ANR-16-CE40-0028). Nadjib Lazaar is supported by the project I3A TRACT (CNRS INSMI INS2I - AMIES - 2018). Mehdi Maamar is supported by the project CPER Data from the region “Hauts-de-France” We thank Yahia Lebbah for the discussions we shared during this work.
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