%0 Journal Article
%T An Improved Frequent Itemsets Mining Algorithm Based on Combination Approach<br>一种基于组合方式改进的频繁项集挖掘算法
%A WANG Cheng-Liang
%A LUO Chang-Yin
%A <br>汪成亮
%A 罗昌银
%J 计算机系统应用
%D 2010
%I 
%X FP-growth algorithm for mining association rules is divided into two phases: building a FP-tree and mining frequent patterns. In this paper new algorithms are proposed to improve the two stages separately. In the first stage, if frequent items in header table have the same support, their position can be dynamically changed to construct a compressed and optimized FP-tree. IMFP-tree algorithm is proposed to realize that function. In the second stage, CFP-mine algorithm is proposed, which constructs pattern-base by using a new method different from the conditional pattern-base in FP-growth.This paper mines frequent itemsets with a new combination method without recursive construction of conditional FP-tree. It has theoretically proved and experimentally verified the correctness and efficiency of CFP-mine algorithm.
%K Association rules
%K FP-tree
%K Frequent itemsets<br>关联规则
%K FP树
%K 频繁项集
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=441A312A5D775A2BED946C79AFDEDF55&yid=140ECF96957D60B2&vid=2A8D03AD8076A2E3&iid=CA4FD0336C81A37A&sid=5D71B28100102720&eid=4F2F18DD6F870C2C&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=6