计算机应用与软件2017，Vol.34Issue(2)：290-294,5.DOI:10.3969/j.issn.1000-386x.2017.02.052
基于前缀项集的Apriori算法改进
THE IMPROVEMENT OF APRIORI ALGORITHM BASED ON PREFIXED-ITEMSET
摘要
Abstract
The mining of association rule is an important method for discovering interesting relations between variables in large databases.Apriori algorithm is one of the most classical algorithms of association rules,but it has bottleneck in efficiency.Thus,a candidate item set storage structure based on prefixed-item set is proposed with the help of the quick search of hash map,and the efficiency of classical Apriori algorithm in connecting and pruning step has been improved greatly.The experiments show that the improved Apriori algorithm does better in efficiency than the classical Apriori algorithm in certain degree's support,and the smaller support,the better efficiency.关键词
数据挖掘/Apriori算法/前缀项集/关联规则/哈希表Key words
Data mining/Apriori algorithm/Prefixed-itemset/Association rules/Hash map分类
信息技术与安全科学引用本文复制引用
于守健,周羿阳..基于前缀项集的Apriori算法改进[J].计算机应用与软件,2017,34(2):290-294,5.
