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Computer Engineering ›› 2009, Vol. 35 ›› Issue (22): 65-67. doi: 10.3969/j.issn.1000-3428.2009.22.022

• Software Technology and Database • Previous Articles     Next Articles

Forecast of Commodities Demand Based on Association Rule of Time Series

ZHANG Jie-xin1,2, ZHANG Lie-ping1   

  1. (1. Academy of Information Science and Engineering, Guilin University of Technology, Guilin 541004; 2. Guangxi Economic Management Cadre College, Nanning 530007)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-11-20 Published:2009-11-20

基于时序关联规则的商品需求预测

章杰鑫1,2,张烈平1   

  1. (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)

Abstract: 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.

Key words: data mining, data model of client mode, rule mode of time series, association rule of time series

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。

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

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