On Pruning Strategies for Discovery of Generalized and Quantitative Association Rules

. Mining association rules has become an important datamining task, and meanwhile many algorithms have been developed which often differ in several aspects. In this paper, we analyse and compare the pruning strategies of several algorithms that were designed for mining generalised and quantitative association rules while abstracting from other technical details. Furthermore, we sketch a novel pruning strategy Genex that exploits all information provided by a taxonomy for pruning and is applicable with a "horizontal" database layout. In the context of mining quantitative association rules, we suggest a novel representation for intervals in terms of interval boundaries. 1 Introduction Mining association rules has become an important datamining task where much research has been conducted and, accordingly, many algorithms have been developed. When first introduced, association rules were restricted to Boolean databases. In the sequel, the original task has been extended in several directi..