DocumentCode :
444007
Title :
Knowledge discovery for goods classification based on rough set
Author :
Zeng, Chuanhua ; Xu, Yang ; Pei, Zheng ; Xie, Weicheng
Author_Institution :
Coll. of Transp. & Automobile Eng., Xihua Univ., Chengdu, China
Volume :
1
fYear :
2005
fDate :
25-27 July 2005
Firstpage :
334
Abstract :
A new method based on rough set theory to classify goods is put forward in this paper. Firstly, we set up a decision table of goods classification; secondly we get some certain rules from this decision table and get a new totally disharmonious decision table by deleting the objects, which can be identified by these certain rules; finally, we get the classification rules from the harmonious decision table according to the principle of minimum risk. By applying these rules, we can classify new goods into its specific class, and decide which method we should employ in the management.
Keywords :
data mining; decision tables; goods distribution; rough set theory; classification rule; decision table; goods classification; knowledge discovery; rough set theory; Artificial intelligence; Computer science; Intelligent control; Inventory management; Knowledge management; Logic; Mathematics; Resource management; Set theory; Transportation; ABC Classification; Rough Set; Rule; Stocks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing, 2005 IEEE International Conference on
Print_ISBN :
0-7803-9017-2
Type :
conf
DOI :
10.1109/GRC.2005.1547298
Filename :
1547298
Link To Document :
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