基于散列的关联规则AprioriTid改进算法

Improvement of AprioriTid Algorithm for Association Rules Based on Hash Technology

发现频繁项集是关联规则挖掘应用的关键,针对采用Apriori类的候选项目集生成-检验方法导致候选项目集产生的代价很高问题,该文提出一种基于散列的快速Apriori Tid改进算法,在Apriori Tid算法的基础上采用基于候选项Lk地址的哈希映射方法,提高了算法的执行效率。

Finding frequent itemset is a pivotal technology and stage in association rules mining application. Most studies adopt Apfiori-like candidate set generation-and-test approach, but candidate set generation is still costly. This paper proposes an improved ApriodTid algorithm to improve the algorithmic executive efficiency, which is based on candidate set Lk address-mapping approach of Hash technology.