AprioriTid挖掘频繁项集算法的改进  

IMPROVEMENT OF APRIORITID ALGORITHM FOR MINING FREQUENT ITEMS

作　　者：兰聪花 刘洋[2] 唐占红 

机构地区：[1]兰州工业高等专科电子信息工程系,甘肃兰州730050 [2]西北民族大学现代教育技术学院,甘肃兰州730030

出　　处：《计算机应用与软件》2010年第3期234-236,共3页Computer Applications and Software

摘　　要：针对AprioriTid算法的不足,提出一种新的优化算法IaprioriTid。该算法从事务压缩、项目压缩和散列技术等方面对AprioriTid算法进行优化,提高了算法的效率。对AprioriTid算法中引入的C′k进行事务压缩和项目压缩,减少C′k中的数据量,提高扫描效率,应用散列技术优化产生频繁-2项集。最后实验证明了该算法的有效性。In this paper a new optimisation algorithm called IapriorTid is proposed against the deficiency of AprioriTid algorithm. The IaprioriTid algorithm optimises the AprioriTid on transactions compression, items compression and hash technology, so improves algorithm＇s efficiency. The imported C′k in ApriofiTid algorithm is exerted the transaction compression and items compression to reduce its data amount, and the scanning efficiency is improved as well, the hash technology is applied for generating the frequent-2 item sets in an optimised way. In the end, the experiment result proves the effectiveness of this algorithm.

关 键 词：频繁项集 APRIORITID算法 事务压缩 项目压缩 散列结构 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]