Abstract
One of the goals of Association Mining is to develop algorithms capable of finding frequently co-occurring groups of items (“itemsets”) in transaction databases. The recently published technique of Itemset Trees expedited the processing of so-called “targeted queries” where the user is interested only in itemsets that contain certain prespecified items. However, the technique did not seem to offer any cost-effective way how to find all frequent itemsets (“general queries”) as it is common with other association-mining algorithms. The purpose of this paper is to rectify this deficiency by a newly developed algorithm that we call IT-Mining. Experimental results indicate that itemset trees can now with advantage be used to answer both targeted and general queries, and that the technique compares favorably with previous atttempts under a broad range of data parameters.