ABSTRACT
Several multi-pass algorithms have been proposed for Association Rule Mining from static repositories. However, such
algorithms are incapable of online processing of transaction streams. In this paper we introduce an efficient single-pass
algorithm for mining association rules, given a hierarchical classification amongst items. Processing efficiency is achieved by
utilizing two optimizations, hierarchy aware counting and transaction reduction, which become possible in the context of
hierarchical classification. We also propose a modified algorithm for the rule generation phase which avoids the construction of
an explicit adjacency lattice.