Methods for Mining Cross Level Association Rule In Taxonomy Data Structures

Mining of association rules mainly focuses at a single conceptual level. In a large database of transaction, where each transaction consists of a set of items, and taxonomy on items, it is required to find out the associations at multiple conceptual levels. In this paper, multilevel association rule mining algorithms have been evaluated and compared. And we will discover additional strong association rules in taxonomy data items. The performance indices used for performance comparisons are minimum support threshold at different levels and varying number of transactions.