PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Filtering association rules with negations on the basis of their confidence boost
José Balcázar, Cristina Tirnauca and Marta E. Zorilla
In: International Conference on Knowledge Discovery and Information Retrieval (KDIR 2010), 25-28 Oct 2010, Valencia, Spain.


We consider a recent proposal to filter association rules on the basis of their novelty: the confidence boost. We develop appropriate mathematical tools to understand it in the presence of negated attributes, and explore the effect of applying it to association rules with negations. We show that, in many cases, the notion of confidence boost allows us to obtain reasonably sized output consisting of intuitively interesting association rules with negations.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:7666
Deposited By:Cristina Tirnauca
Deposited On:17 March 2011