New algorithm of mining frequent closed itemsets  

一种新的频繁闭项目集挖掘算法(英文)

作　　者：张亮[1] 任永功[1] 付玉[1] 

机构地区：[1]辽宁师范大学计算机与信息技术学院,大连116029

出　　处：《Journal of Southeast University(English Edition)》2008年第3期335-338,共4页东南大学学报（英文版）

基　　金：The National Natural Science Foundation of China(No.60603047);the Natural Science Foundation of Liaoning Province;Liaoning Higher Education Research Foundation(No.2008341)

摘　　要：A new algorithm based on an FC-tree （frequent closed pattern tree） and a max-FCIA （maximal frequent closed itemsets algorithm） is presented, which is used to mine the frequent closed itemsets for solving memory and time consuming problems. This algorithm maps the transaction database by using a Hash table,gets the support of all frequent itemsets through operating the Hash table and forms a lexicographic subset tree including the frequent itemsets.Efficient pruning methods are used to get the FC-tree including all the minimum frequent closed itemsets through processing the lexicographic subset tree.Finally,frequent closed itemsets are generated from minimum frequent closed itemsets.The experimental results show that the mapping transaction database is introduced in the algorithm to reduce time consumption and to improve the efficiency of the program.Furthermore,the effective pruning strategy restrains the number of candidates,which saves space.The results show that the algorithm is effective.为了解决频繁闭项目集挖掘中时间和存储开销大的问题,提出了一种基于FC-tree(频繁闭模式树)的频繁闭项目集挖掘算法max-FCIA(最大频繁闭项目集挖掘算法).该算法利用哈希表映射事务数据库,通过对哈希表进行操作从而得到所有频繁项目集的支持度,进而生成包含所有频繁项目的有序树.经过剪枝处理的有序树就是包含所有最小频繁闭项目集的FC-tree,最后用最小频繁闭项目集生成频繁闭项目集.实验结果表明,该算法通过映射事务数据库,减少了扫描数据库所浪费的时间,提高程序执行效率.另外,运用有效的剪枝策略,避免了不必要候选项目集的生成,节省了存储空间,实验证明该算法是有效的.

关 键 词：frequent itemsets frequent closed itemsets minimum frequent closed itemsets maximal frequent closed itemsets frequent closed pattern tree 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]