DocumentCode :
3255427
Title :
An algorithm for reusable uninteresting rules in association rule mining
Author :
Thongtae, Pongsiam ; Srisuk, Sanun
Author_Institution :
Dept. of Comput. Eng., Mahanakorn Univ. of Technol., Bangkok
fYear :
2008
fDate :
4-6 Aug. 2008
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, we present a new framework for reusable association rule mining based on chi2 and odds ratio. We start at mining the association rules using standard Apriori algorithm. The strong rules are defined as association rules, while the weak rules will be evaluated by our proposed method. Firstly, the weak rules must be converted to 2 times 2 contingency table. We then compute the relationship between variables using chi2 and odds ratio. If the weak rules are related to each other with positive or negative relationship, then the weak rules will also be determined as association rules. Our system is evaluated with experiments on the crime data.
Keywords :
data mining; contingency table; reusable association rule mining; reusable uninteresting rules; standard apriori algorithm; weak rules; Association rules; Data mining; Itemsets; Pattern analysis; Testing; Transaction databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applications of Digital Information and Web Technologies, 2008. ICADIWT 2008. First International Conference on the
Conference_Location :
Ostrava
Print_ISBN :
978-1-4244-2623-2
Electronic_ISBN :
978-1-4244-2624-9
Type :
conf
DOI :
10.1109/ICADIWT.2008.4664326
Filename :
4664326
Link To Document :
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