One of the most challenging problems in data manipulation in the future is to be able to e ciently handle very large databases but also multiple induced properties or generalizatio...
In data mining, enumerate the frequent or the closed patterns is often the first difficult task leading to the association rules discovery. The number of these patterns represen...
We present a multi-objective genetic algorithm for mining highly predictive and comprehensible classification rules from large databases. We emphasize predictive accuracy and comp...
As the first stage for discovering association rules, frequent itemsets mining is an important challenging task for large databases. Sampling provides an efficient way to get appro...
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...