Title :
Research of data mining based on Apriori algorithm in cutting database
Author :
Wang, Guofeng ; Yu, Xiu ; Peng, Dongbiao ; Cui, Yinhu ; Li, Qiming
Author_Institution :
Sch. of Mech. Eng., Tianjin Univ., Tianjin, China
Abstract :
Cutting data mining is an important method to increase efficiency, discover hidden knowledges in cutting database, and provide guidance for cutting decisions. This paper analyze the Apriori algorithm for association rules mining, and make some improvement for this algorithm based on the features of cutting database. Apriori algorithm is improved to mine association rules in cutting database. The results show that the Apriori algorithm can be efficiently used in cutting data mining, and improved algorithm can achieve expected effect better than traditional algorithm.
Keywords :
cutting; data mining; apriori algorithm; association rules mining; cutting database; data mining; knowledge discovery; Algorithm design and analysis; Arithmetic; Association rules; Data mining; Explosives; Machining; Mechanical engineering; Power generation economics; Spatial databases; Apriori algorithm; association rules mining; cutting database; data mining;
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7737-1
DOI :
10.1109/MACE.2010.5535790