In this work we focus on the problem of frequent itemset mining on large, out-of-core data sets. After presenting a characterization of existing out-of-core frequent itemset minin...
Subspace clustering and frequent itemset mining via “stepby-step” algorithms that search the subspace/pattern lattice in a top-down or bottom-up fashion do not scale to large ...
Abstract. The explosion of data stored in commercial or administrational databases calls for intelligent techniques to discover the patterns hidden in them and thus to exploit all ...
The randomized response (RR) technique is a promising technique to disguise private categorical data in Privacy-Preserving Data Mining (PPDM). Although a number of RR-based methods...
Abstract. A new algorithm is presented for finding genotype-phenotype association rules from data related to complex diseases. The algorithm was based on Genetic Algorithms, a tech...
Vanessa Aguiar, Jose A. Seoane, Ana Freire, Cristi...