In this paper we propose a method for grouping and summarizing large sets of association rules according to the items contained in each rule. We use hierarchical clustering to par...
Spatial associative classification takes advantage of employing association rules for spatial classification purposes. In this work, we investigate spatial associative classificati...
Abstract. We analyse data from the Edinburgh Mouse Atlas GeneExpression Database (EMAGE) which is a high quality data source for spatio-temporal gene expression patterns. Using a n...
Time series pattern mining (TSPM) finds correlations or dependencies in same series or in multiple time series. When the numerous instances of multiple time series data are associ...
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
Evelina Lamma, Fabrizio Riguzzi, Andrea Stambazzi,...