We focus on the problem of finding patterns across two large, multidimensional datasets. For example, given feature vectors of healthy and of non-healthy patients, we want to answ...
Agma J. M. Traina, Caetano Traina Jr., Spiros Papa...
The automatic induction of classification rules from examples in the form of a decision tree is an important technique used in data mining. One of the problems encountered is the o...
Real-world datasets exhibit a complex dependency structure among the data attributes. Learning this structure is a key task in automatic statistics configuration for query optimi...
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
We consider the problem of finding association rules that make nearly optimal binary segmentations of huge categorical databases. The optimality of segmentation is defined by an o...