DocumentCode :
2335736
Title :
Application of data mining in supply chain management
Author :
An Chen ; Lu Liu ; Ning, Chen ; Guoping, Xia
Author_Institution :
Sch. of Manage., Beijing Univ. of Aeronaut. & Astronaut., China
Volume :
3
fYear :
2000
fDate :
2000
Firstpage :
1943
Abstract :
Dealing with the very large database in supply chain management is a very important problem. Mining association rules and sequential patterns from large database has been recognized by many researchers in database systems and many other related management areas. In this paper, the research on data mining of supply chain is first introduced, then the four stages of the implementation of data mining are given. Many previous works focus on mining association rules in transaction database and sequential patterns at a single concept level, but there exists many phenomena of multiple level sequence patterns in practice. An effective multiple sequence patterns mining algorithm is presented in this paper. Finally, a case study is discussed
Keywords :
data mining; manufacturing data processing; stock control data processing; very large databases; association rule mining; data mining; knowledge discovery; multiple level sequence patterns; supply chain management; very large database; Association rules; Data mining; Database systems; Mathematics; Pattern recognition; Supply chain management; Supply chains; Transaction databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
Type :
conf
DOI :
10.1109/WCICA.2000.862854
Filename :
862854
Link To Document :
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