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Conference Papers Year : 2021

Constraint Programming for Itemset Mining with Multiple Minimum Supports

Abstract

The problem of discovering frequent itemsets including 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.
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Dates and versions

lirmm-03520973 , version 1 (11-01-2022)

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Mohamed-Bachir Belaid, Nadjib Lazaar. Constraint Programming for Itemset Mining with Multiple Minimum Supports. ICTAI 2021 - 33rd IEEE International Conference on Tools with Artificial Intelligence, Nov 2021, Washington, DC, United States. pp.598-603, ⟨10.1109/ICTAI52525.2021.00095⟩. ⟨lirmm-03520973⟩
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