DocumentCode :
1688736
Title :
The dynamic data reduction and association rule parallel mining based on rough set
Author :
Youquan, He ; LiJun, Wang
Author_Institution :
Inf. Sci. & Eng. Dept., Chongqing Jiaotong Univ., Chongqing, China
fYear :
2010
Firstpage :
2803
Lastpage :
2806
Abstract :
To dynamic increasing databases, the data dynamic reduction and decision-making rule mining are treated by the methods of repeat scan, order, search, reduction data set traditionally, this paper proposes a new mining algorithm, which treat two dispart table simultaneously by using program´ many course parallel technology. This method improves greatly mining efficiency of the system, is of important reference meaning to data reduction and association rule mining of the large dynamic increasing databases.
Keywords :
data mining; data reduction; decision making; parallel processing; rough set theory; association rule; decision making rule mining; dispart table; dynamic data reduction; parallel mining; rough set; Association rules; Bioinformatics; Databases; Heuristic algorithms; Information science; Rough sets; association rule; data mining; data reduction; parallel mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
Type :
conf
DOI :
10.1109/WCICA.2010.5554493
Filename :
5554493
Link To Document :
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