DocumentCode :
443985
Title :
An algorithm of association rules extracting based on granular computing and its application
Author :
Qiu, Taorong ; Chen, Xiaoqing ; Liu, Qing ; Huang, Houkuan
Author_Institution :
Sch. of Comput. & Inf. Technol., Beijing Jiaotong Univ., China
Volume :
1
fYear :
2005
fDate :
25-27 July 2005
Firstpage :
225
Abstract :
In this paper, on the basis of the Apriori algorithm, a granular computing-based algorithm for association rules extracting is presented. The comparison of the running time between the presented algorithm and the Apriori algorithm is discussed, and its running procedure is illustrated by a real world example. By analyzing, it is shown that the granular computing-based algorithm for association rules extracting reduces efficiently the number of candidate elements, and avoids scanning repeatedly the information table.
Keywords :
data mining; fuzzy set theory; Apriori algorithm; association rule extraction; data mining; fuzzy set theory; granular computing-based algorithm; Algorithm design and analysis; Association rules; Clustering algorithms; Computer applications; Data mining; Information analysis; Information technology; Monitoring; Pattern analysis; Stock markets; association rules; data mining; granular computing;
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.2005.1547272
Filename :
1547272
Link To Document :
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