DocumentCode :
2121458
Title :
An Algorithm of Association Rules Mining Based on Restricted Conditional Probability Distribution
Author :
Cao, Wenliang ; Hu, Xuanzi ; Liu, Fasheng
Author_Institution :
Dept. of Comput. Eng., DongGuan Polytech., Dongguan, China
fYear :
2010
fDate :
24-26 Dec. 2010
Firstpage :
517
Lastpage :
520
Abstract :
There are excessive and disordered rules generated by traditional approaches of association rule mining, many of which are redundant, so that they are difficult for users to understand and make use of. Agrawal et al pointed out the bottleneck of transaction number increase association rules according to the index increase. To solve this problem, a new method was represented, which is based on restricted conditional probability distribution to get a condensed rules set by removing redundant rules. Our set of rules is more meaningful, more concise and users are interested in than others. Especially, the number of rules in rules-set has been reduced greatly. We find that it is an effective method of association rules mining from examples, finally poses future research.
Keywords :
data mining; statistical distributions; association rules mining algorithm; restricted conditional probability distribution; rules-set; Algorithm design and analysis; Association rules; Itemsets; Presses; Probability distribution; Association Rules; Data Mining; Restricted Conditional Probability Distribution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ISISE), 2010 International Symposium on
Conference_Location :
Shanghai
ISSN :
2160-1283
Print_ISBN :
978-1-61284-428-2
Type :
conf
DOI :
10.1109/ISISE.2010.130
Filename :
5945159
Link To Document :
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