When companies seek for the combination of products which can constantly generate high profit, the association rule mining (ARM) or the utility mining will not achieve such task. ...
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...
Levelwise algorithms (e.g., the Apriori algorithm) have been proved eective for association rule mining from sparse data. However, in many practical applications, the computation ...
Sequential pattern mining aims to find frequent patterns (guarded by a minimum support) in a database of sequences. As the support decreases the number of sequential patterns will...
High dimensionality remains a significant challenge for document clustering. Recent approaches used frequent itemsets and closed frequent itemsets to reduce dimensionality, and to...