摘要
Apriori算法是一种经典的关联分析挖掘算法.经典Apriori算法计算效率偏低,并且需要多次扫描数据库.针对这些问题,文章提出了基于Hash表改进的Apriori算法.基于Hash表的改进Apriori算法计算时只需扫描对应频繁项集Hash表中对应的项,缩小了扫描范围,并且只需要扫描一次数据库.对比经典的Apriori算法,性能具有显著提高.
Apriori algorithm is a classic association analysis mining algorithm,but the Apriori algorithm is inefficient and requires multiple scans in the database.In response to these problems,an Improved Apriori Algorithm Based on Hash Tables is proposed here.When the Improved Apriori Algorithm Based on the Hash Tables is calculating,only the corresponding items in the corresponding frequent itemset Hash table need to be scanned,the scanning range is reduced,the calculation efficiency is improved significantly,and the database needs to be only scanned once.Compared with the classic Apriori algorithm,the performance is significantly improved.
作者
钟育彬
李健标
ZHONG Yu-bin;LI Jian-biao(School of Mathematics and Information Sciences,Guangzhou University,Guangzhou 510006,China)
出处
《广州大学学报（自然科学版）》
CAS
2018年第6期7-9,共3页
Journal of Guangzhou University:Natural Science Edition
