An interactive discovery method for finding association rules is presented. It consists in a user-guided search using reduction operators on a rule. Rules are generated on-demand according to the navigation made by the user. Main interest of this approach is that, at each step, the user has only a linear number of new rules to analyse and that all computations are done in polynomial time. Sever...

We consider the problem of clustering two-dimensional association rules in large databases. We present a geometricbased algorithm, BitOp, for performing the clustering, embedded within an association rule clustering system, ARCS. Association rule clustering is useful when the user desires to segment the data. We measure the quality of the segmentation generated by ARCS using the Minimum Descrip...