DocumentCode :
3509570
Title :
Design and Application of Intelligent Reasoning Module Based on Rough Set
Author :
Yang, Zu-qiao ; LIU, Gui-mei ; XIAO, Xiao-hong ; Gao, Han-ping
Author_Institution :
Sch. of Comput. Sci. & Technol., HuangGang Normal Univ., Huanggang, China
fYear :
2010
fDate :
28-29 Oct. 2010
Firstpage :
663
Lastpage :
666
Abstract :
To enhance the ability of intelligent reasoning and decision-making modules of present MIS, an algorithm is proposed which using rough set to reduce sampling data and produce rule library. It is done by giving a knowledge reduction and rule extraction algorithm based on a comprehensive analysis of rough set theory and present algorithms, taking a comprehensive evaluation database of university students as samples to extract rules, designing and accomplishing an intelligent module for MIS. Results of practical examples show that this algorithm can effectively process students sampling data and acquire a lot of useful knowledge rules. These rules can provide powerful decision support for managers, and effectively realize intelligent reasoning in IMIS.
Keywords :
data mining; decision making; decision support systems; inference mechanisms; rough set theory; MIS; decision making; decision support; intelligent reasoning module; knowledge reduction algorithm; knowledge rules; rough set theory; rule extraction algorithm; Approximation methods; Artificial intelligence; Cognition; Data mining; Decision making; Set theory; Symmetric matrices; information management system; intelligent reasoning; rough set; rule extraction and optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligence Information Processing and Trusted Computing (IPTC), 2010 International Symposium on
Conference_Location :
Huanggang
Print_ISBN :
978-1-4244-8148-4
Electronic_ISBN :
978-0-7695-4196-9
Type :
conf
DOI :
10.1109/IPTC.2010.31
Filename :
5662871
Link To Document :
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