基于单次扫描无构造调节的频繁模式挖掘算法  

Algorithm for Mining Frequent Patterns Based on the Single Scan Without Structure Adjustment

作　　者：刘芝怡[1] 

机构地区：[1]常州工学院计算机信息工程学院,江苏常州213002

出　　处：《科技通报》2014年第6期119-121,共3页Bulletin of Science and Technology

摘　　要：研究频繁项集模式挖掘优化问题。传统的挖掘算法常产生大规模的候选项集,并且反复扫描数据库,导致频繁项集挖掘时间过长,空间效率太低。为了改进频繁项集挖掘时时间与空间效率低的问题,提出一种高效频繁项集挖掘算法CPT-Mine。此算法利用编码模式树存储事务数据库中的频繁项集信息,构建FP数组,加快产生频繁项集,引入CPT-Mine算法,快速地挖掘数据库中所包含的频繁项集,无需递归构造条件模式树,只需两次扫描数据库即可生成所有频繁项集。最后的实验证明了该算法能缩短挖掘时间3～10 s,空间效率提高43%。The frequent itemsets mining optimization model is researched. Traditional mining is often produce large-scale candidate itemsets, and repeatedly scanning database, the time is too long, lead to frequent itemsets mining space efficien-cy is too low. Frequent itemset mining is to improve the problem of low efficiency of time and space, put forward an efficient algorithm for mining frequent itemsets CPT-Mine. The algorithm using encoding scheme tree store information of frequent itemsets of transaction databases construction of FP array, to speed up the produce frequent itemsets, the introduction of CPT-Mine algorithm, fast, frequent itemsets mining database contains no recursive model tree structure conditions, only two times of scanning database can generate all frequent itemsets. The experiment proves that this algorithm can shorten the mining time 3~10 s, space efficiency increased by 43%.

关 键 词：频繁项集 编码模式树 素数编码 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]