基于时序关联规则的商品需求预测  

Forecast of Commodities Demand Based on Association Rule of Time Series

作　　者：章杰鑫[1,2] 张烈平[1] 

机构地区：[1]桂林理工大学信息科学与工程学院,桂林541004 [2]广西经济管理干部学院,南宁530007

出　　处：《计算机工程》2009年第22期65-67,共3页Computer Engineering

基　　金：广西自然科学基金资助项目(桂科自0991252)

摘　　要：为了满足商品销售企业对商品需求预测的需求,提出一种时序关联规则挖掘算法。利用企业商品销售数据与客户相关的特点,提出客户模式数据模型,针对该数据模型,给出时序关联规则挖掘算法。利用该算法对超市销售数据进行时序关联规则挖掘,得到了正确的结果,验证了其在实际应用中的有效性。In order to meet the corporations＇ demand of forecast of commodities demand, this paper proposes an association rule of time series mining algorithm, which combines with temporal association rules. It uses the characteristic that commodities sale is relation to the clients to present a data model definition, and accordance with the data mould to propose an association rule of time series mining algorithm. It uses the mining algorithm to deal with the data of supermarket and achieves the right result, which proves the validity of the algorithm.

关 键 词：数据挖掘 客户模式数据模型 时序规则模式 时序关联规则 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]