计算机系统应用
計算機繫統應用
계산궤계통응용
APPLICATIONS OF THE COMPUTER SYSTEMS
2010年
1期
67-71
,共5页
关联规则%FP树%频繁项集
關聯規則%FP樹%頻繁項集
관련규칙%FP수%빈번항집
Association rules%FP-tree%Frequent itemsets
FP-growth算法用于关联规则挖掘分成两个阶段:构建频繁模式树和进行频繁模式挖掘;对这两个阶段分别进行改进,若项头表中存在同频度的频繁项,在构建FP-tree的过程动态调整其位置,构建压缩的最优化FP-tree,提出了IMFP-tree算法.在进行频繁模式挖掘阶段,提出CFP-mine算法,CFP-mine算法采用一种新方法构建条件模式基,且采用组合方式挖掘频繁项集,有别于传统FP-growth算法的挖掘过程,理论上证明和实验验证本算法的正确性和高效性.
FP-growth算法用于關聯規則挖掘分成兩箇階段:構建頻繁模式樹和進行頻繁模式挖掘;對這兩箇階段分彆進行改進,若項頭錶中存在同頻度的頻繁項,在構建FP-tree的過程動態調整其位置,構建壓縮的最優化FP-tree,提齣瞭IMFP-tree算法.在進行頻繁模式挖掘階段,提齣CFP-mine算法,CFP-mine算法採用一種新方法構建條件模式基,且採用組閤方式挖掘頻繁項集,有彆于傳統FP-growth算法的挖掘過程,理論上證明和實驗驗證本算法的正確性和高效性.
FP-growth산법용우관련규칙알굴분성량개계단:구건빈번모식수화진행빈번모식알굴;대저량개계단분별진행개진,약항두표중존재동빈도적빈번항,재구건FP-tree적과정동태조정기위치,구건압축적최우화FP-tree,제출료IMFP-tree산법.재진행빈번모식알굴계단,제출CFP-mine산법,CFP-mine산법채용일충신방법구건조건모식기,차채용조합방식알굴빈번항집,유별우전통FP-growth산법적알굴과정,이론상증명화실험험증본산법적정학성화고효성.
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 dynamiffally 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 conistruction of conditional FP-tree.It has theoretically proved and experimentally verified the correctness and efficiency of CFP-mine algorithm.
