基于约束的多维Apriori改进算法  

Algorithm of multi-dimensional Apriori with constraints

作　　者：王志昊 苏明月 李东方 沈炜 杨光 Wang Zhihao;Su Mingyue;Li Dongfang;Shen Wei;Yang Guang(Institute 706,Second Academy of China Aerospace Science and Industry Corporation,Beijing 100854,China)

机构地区：[1]北京计算机技术及应用研究所,北京100854

出　　处：《电子技术应用》2023年第10期100-105,共6页Application of Electronic Technique

摘　　要：针对经典多维关联规则挖掘算法执行效率不高、存在冗余规则的不足,提出基于约束的多维Apriori改进算法,在多维Apriori算法的基础上,将用户约束引入挖掘过程,根据关于谓词的约束产生用户感兴趣的频繁谓词集,并以此为依据删减事务集。该算法一方面通过用户约束大大缩减了候选谓词集的产生,另一方面经过删减的事务集也降低了扫描数据库的开销,最终实现了挖掘效率的提高以及冗余规则的减少。应用该算法在FPGA代码缺陷事务集上进行对比实验,实验结果证明了该算法相比多维Apriori算法,在搜索效率以及挖掘结果的准确性方面均得到了改善,有效提高了FPGA代码缺陷分析的准确性。Aiming at the inefficiency of multi-dimensional association rules mining algorithm and the existence of redundant rules,an algorithm of multi-Dimensional apriori with constraints is proposed.Based on the multi-dimensional Apriori algorithm,the algorithm controls the mining process with user constraints.According to the predicate constraint,the frequent predicate set that is of interest to the user is generated,and the transaction set is deleted based on the predicate constraint.On the one hand,the algorithm greatly reduces the generation of candidate predicate sets through user constraints.On the other hand,the reduced transaction set also reduces the scanning database overhead.Finally,the efficiency of mining is improved and the redundant rules are reduced.This algorithm is used to compare experiments on FPGA code defect transaction sets.The experimental results show that compared with the multi-dimensional Apriori algorithm,this algorithm has improved the search efficiency of frequent predicate sets and the accuracy of mining results.

关 键 词：关联规则挖掘 多维关联规则 APRIORI算法 频繁谓词集 谓词约束 数据挖掘 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]