DocumentCode
460684
Title
Rules Mining From Large Datasets Based on Rough Set
Author
Xiang-gong, Hong ; Zhiyan, Wang ; Sen, Guo ; Ping, Wang
Author_Institution
Sch. of Inf. Eng., NanChang Univ.
Volume
3
fYear
2006
fDate
25-28 June 2006
Firstpage
2119
Lastpage
2123
Abstract
The existing rough set based methods are not applicable for large data sets because of the high time and space complexity. In this paper, a new algorithm, called R_Apriori, is presented by which large data sets are divided into several parts, in combination with a priori algorithm, implicated rules are derived in liner relation to size of data set. At last, this result is proved by experiments based on three classical UCI repositories
Keywords
data mining; rough set theory; R_Apriori algorithm; data mining; rough set based method; Algorithm design and analysis; Association rules; Computer science; Data engineering; Data mining; Database systems; Information systems; Knowledge representation; Set theory; Space technology;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications, Circuits and Systems Proceedings, 2006 International Conference on
Conference_Location
Guilin
Print_ISBN
0-7803-9584-0
Electronic_ISBN
0-7803-9585-9
Type
conf
DOI
10.1109/ICCCAS.2006.284917
Filename
4064323
Link To Document