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RNTI

MODULAD
Représentation condensée de règles d’association multidimensionnelles
In EGC 2019, vol. RNTI-E-35, pp.225-236
Abstract
Association rules mining is a problem that gave rise to a rich literature, especially in classic
binary bidimensional data. In particular, the relation between closed sets and association rules
is well understood. This is not the case in multidimensional data. In this paper, we show that
the knowledge of the closed n-sets of a multidimensional boolean tensor is enough to allow
for the derivation of the confidence of every multidimensional association rule.