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浙江大学学报(工学版)
J4  2009, Vol. 43 Issue (12): 2259-2263    DOI: 10.3785/j.issn.1008-973X.2009.12.023
工业工程与制造业信息化     
基于频繁模式挖掘的实时供应链数据分析
田景红,潘晓弘,王正肖
（浙江大学 现代制造工程研究所,浙江省先进制造技术重点研究实验室,浙江 杭州 310027）
Data analysis in real-time supply chain based on frequent pattern mining
TIAN Jing-hong, PAN Xiao-hong, WANG Zheng-xiao
(Institute of Manufacturing Engineering, Zhejiang Province Key Laboratory of Advanced Manufacturing Technology, Zhejiang University, Hangzhou 310027,China)
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摘要：

为了从海量的供应链实时数据中发掘隐性的、重要的业务关系,将频繁模式挖掘(FPM)引入到供应链实时数据分析,有利于提高决策的科学性与效率.提出了实时供应链体系结构,包括数据采集层、实时数据处理层与实时供应链应用层,阐述了实时数据采集与处理、频繁路径选择及频繁模式挖掘的方法.详细论述了频繁路径选择、工作流立方建立及频繁模式挖掘3个阶段实时数据处理的内容、原理与方法.结合某服装供应链分销管理,应用DBMiner工具进行了实证研究,结果表明,应用FPM技术进行供应链实时数据分析,可以高效地挖掘与利用实时数据,提高供应链运作的效率与供应链决策水平.
Abstract:

In order to discover the hidden and important business relation, frequent pattern mining (FPM) was introduced into the field of real-time data analysis, which can improve the scientificity and efficiency of supply chain decision. The real-time supply chain framework was proposed, which include data capturing layer, real-time data processing layer, and real-time supply chain application layer. The methods of real-time data capturing and processing, frequent path selection, and frequent pattern mining were discussed. Real-time data processing content, principles and methods in frequent path selection, workflow cube and frequent pattern mining were expounded. A case study of distribution management in some clothes supply chain was conducted with DBMiner tools. Results show that FPM can efficiently mine and exploit real-time data and enhance the efficiency of supply chain operation and the level of supply chain decision.
出版日期: 2010-01-16
:  TP 278  
基金资助:

国家“863”高技术研究发展计划资助项目（2009AA04Z151）, 浙江省科技计划资助项目（2006C11237）.
通讯作者: 王正肖,男,副教授.     E-mail: wangzhengxiao@zju.edu.cn
作者简介: 田景红（1976-）,男,重庆人,博士生,主要从事供应链管理、物流管理的研究.
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引用本文:

田景红, 潘晓弘, 王正肖. 基于频繁模式挖掘的实时供应链数据分析[J]. J4, 2009, 43(12): 2259-2263.

TIAN Jing-Gong, BO Xiao-Hong, WANG Zheng-Xiao. Data analysis in real-time supply chain based on frequent pattern mining. J4, 2009, 43(12): 2259-2263.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2009.12.023    或    http://www.zjujournals.com/eng/CN/Y2009/V43/I12/2259


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