Frequent pattern mining on data streams is of interest recently. However, it is not easy for users to determine a proper frequency threshold. It is more reasonable to ask users to ...
Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...
Existing algorithms for mining association patterns often rely on the support-based pruning strategy to prune a combinatorial search space. However, this strategy is not effective ...
While scalable data mining methods are expected to cope with massive Web data, coping with evolving trends in noisy data in a continuous fashion, and without any unnecessary stopp...
This paper presents some new algorithms to efficiently mine max frequent generalized itemsets (g-itemsets) and essential generalized association rules (g-rules). These are compact ...