In this paper, we study the maintenance of frequent patterns in the context of the generator representation. The generator representation is a concise and lossless representation o...
When training classifiers, presence of noise can severely harm their performance. In this paper, we focus on “non-class” attribute noise and we consider how a frequent fault-t...
The discovery of frequent patterns is a famous problem in data mining. While plenty of algorithms have been proposed during the last decade, only a few contributions have tried to...
Abstract. The paradigm of pattern discovery based on constraints was introduced with the aim of providing to the user a tool to drive the discovery process towards potentially inte...
Recent research in frequent pattern mining (FPM) has shifted from obtaining the complete set of frequent patterns to generating only a representative (summary) subset of frequent ...