Online monitoring of data streams poses a challenge in many data-centric applications, such as telecommunications networks, traffic management, trend-related analysis, webclick st...
This paper proposes a prefix-tree structure, called CPS-tree (Compact Pattern Stream tree) that efficiently discovers the exact set of recent frequent patterns from high-speed dat...
The issue addressed in this paper concerns the discovery of frequent multi-dimensional patterns from relational sequences. The great variety of applications of sequential pattern m...
Floriana Esposito, Nicola Di Mauro, Teresa Maria A...
We propose a generic framework that uses utility in decision making to drive the data mining process. We use concepts from meta-learning and build on earlier work by Elovici and B...
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...