Some challenges in frequent pattern mining from data streams are the drift of data distribution and the computational efficiency. In this work an additional challenge is considered...
Fabio Fumarola, Anna Ciampi, Annalisa Appice, Dona...
Aggregate monitoring over data streams is attracting more and more attention in research community due to its broad potential applications. Existing methods suffer two problems, 1...
Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
Continuous queries applied over nonterminating data streams usually specify windows in order to obtain an evolving –yet restricted– set of tuples and thus provide timely result...
Mining generator patterns has raised great research interest in recent years. The main purpose of mining itemset generators is that they can form equivalence classes together with...