AuthorsM. B. Belaid and N. Lazaar
TitleConstraint Programming for Itemset Mining with Multiple Minimum Supports
AfilliationSoftware Engineering
Project(s) Testing of Learning Robots (T-LARGO) , Testing of Learning Robots (T-Largo), Department of Validation Intelligence for Autonomous Software Systems
StatusAccepted
Publication TypeProceedings, refereed
Year of Publication2021
Conference NameICTAI
Publisher IEEE
Abstract

The problem of discovering frequent itemsets includ- ing rare ones has received a great deal of attention. The mining process needs to be flexible enough to extract frequent and rare regularities at once. On the other hand, it has recently been shown that constraint programming is a flexible way to tackle data mining tasks. In this paper, we propose a constraint programming approach for mining itemsets with multiple minimum supports. Our approach provides the user with the possibility to express any kind of constraints on the minimum item supports. An experimental analysis shows the practical effectiveness of our approach compared to the state of the art.

Citation Key28048

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