一种快速有效的分布式开采多层关联规则的算法

关联规则（association rules）是数据开采的重要研究内容，建立项目的层次关系可以发现更加有意义的规则，主要研究分布式环境下开采多层关联规则的问题，提出了一种快速有效的ＭＬＦＤＭ算法，采用的技术包括分布式编码交易表的有效修剪，侯选集的产生及修剪技术，侯选项集的全局支持数的计算方法等，论述了它的原理，具体实现方法及其几个改进算法，实验结果表明，算法ＭＬＦＤＭ是有效的，并对ＭＬＦＤＭ算法的几个变种进行了讨论。

A DISTRIBUTED ALGORITHM FOR MINING MULTILEVEL ASSOCIATION RULES

Association rule mining is an important task of data mining. In general an item is part of a hierarchy. More interesting rules can be found based on information taxonomy. The problem of multilevel association rule mining under distributed environment is studied, and a fast algorithm called MLFDM is proposed. Several techniques used in the algorithm are introduced, including encoded transaction table pruning, candidate iternsets generating and pruning, and the support count computing, etc. The principles and implementation and several variants of the algorithm are also discussed. The experiments prove the efficiency of these algorithms.