Mining multilevel association rules with dynamic concept hierarchy

Association rule mining has attracted wide attention in both research and application areas recently. The mining of multilevel association rules is one of the important branches of it. In most of the studies, multilevel rules will be mined through repeated mining from databases or mining the rules at each individually levels, it affects the efficiency, integrality and accuracy. In this paper, a novel method is proposed to improve this situation by analyzing the rules mined from primitive concept level to obtain multilevel rules. The proposed method also supports dynamic concept hierarchies.