基于协方差的FP-Growth算法在ERP中的研究与应用  

FP-Growth Algorithm Based Covariance and Its Application in ERP

作　　者：曾安平[1] 黄永平[2] 李广军[1] 阳万安[1] 唐自力[1] 

机构地区：[1]四川宜宾学院计科系,宜宾644007 [2]四川宜宾学院物电系,宜宾644007

出　　处：《数学的实践与认识》2008年第12期11-18,共8页Mathematics in Practice and Theory

基　　金：四川省宜宾市科技局科研基金(200702036);宜宾学院青年基金(QJ05-08)

摘　　要：文章简要介绍了关联规则挖掘技术,通过对经典算法FP-Growth在某鞋业ERP系统中的应用分析,发现了FP-Growth算法挖掘的部分数据无用的缺陷,提出了一种增加协方差兴趣度阈值的改进算法—CovFP-Growth算法.该算法采用协方差的概念,能够更准确地挖掘出交易集中不同产品间的紧密相关性,减少产生的无用规则,为ERP的产品预测计划决策提供了良好的理论依据和实现方法.This paper introduces association rules mining technology briefly. By analyzing the application of classic FP-Growth algorithm in ERP System, and finds out FP-Growth algorithm＇s limitation which often generates some useless datas. So this paper gives a CovFP- Growth algorithm Based covariance Measure for Updating FP-Growth. Using the covariance method, CovFP-Growth can mine the close relations among different products in the database, decrease the amount of useless rules and provide effective assistant method for the generating of prediction plan.

关 键 词：协方差 兴趣度 关联规则 FP—Growth CovFP—Growth ERP 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]