Mining frequent patterns in a data stream is very challenging for the high complexity of managing patterns with bounded memory against the unbounded data. While many approaches as...
A major challenge in frequent-pattern mining is the sheer size of its mining results. To compress the frequent patterns, we propose to cluster frequent patterns with a tightness m...
We study the problem of finding frequent items in a continuous stream of itemsets. A new frequency measure is introduced, based on a flexible window length. For a given item, its ...
Mining fault tolerant (FT) frequent patterns from transactional datasets are very complex than mining all frequent patterns (itemsets), in terms of both search space exploration a...
In this paper, we devise a method for the estimation of the true support of itemsets on data streams, with the objective to maximize one chosen criterion among {precision, recall}...
Pierre-Alain Laur, Richard Nock, Jean-Emile Sympho...