基于多层关联规则挖掘的超市货架陈列优化  

Optimization of Supermarket Shelf Display Based on Multilevel Association Rules Mining

作　　者：蔡芬[1] 

机构地区：[1]泉州师范学院,福建泉州362000

出　　处：《东莞理工学院学报》2014年第5期42-47,共6页Journal of Dongguan University of Technology

基　　金：福建省教育厅"数据挖掘在泉州企业供应链管理系统中的应用"(JA10240)

摘　　要：基于.NET架构和数据仓库技术开发经理人决策支持平台,使用多层关联规则算法挖掘购物小票的频繁项集,发现顾客的购物模式,为超市货架陈列优化提供帮助。文章分析了决策支持平台的体系设计,多层关联规则挖掘模型的设计,最后进行频繁项集和规则的挖掘示例,并给出超市货架陈列的优化建议。The system develops a Manager Decision Support Platform based on Net Structure and Data Warehouse Technology. It uses Multilevel Association Rules Algorithm to mine the Frequent-item Set of shopping receipt,to find out the shopping pattern of customers,so as to provide assistance for the optimization of supermarket shelves displaying. This essay analyzes the structure design of Decision Support Platform and the Mining Model Design of Multilevel Association Rules,providing the mining example of Frequent-item Set,as well as giving some suggestions on the optimization of supermarket shelves display.

关 键 词：数据挖掘 多层关联规则 垂直数据格式 超市决策支持系统 

分 类 号：TP31[自动化与计算机技术—计算机软件与理论]