DocumentCode :
2189958
Title :
Association Rule Algorithms for Logical Equality Relationships
Author :
Chen, Chyuan-Meei ; Liao, Shu-Hsien
Author_Institution :
Tamkang Univ., Danshuei
fYear :
2008
fDate :
8-11 July 2008
Firstpage :
26
Lastpage :
30
Abstract :
The association rule has become one of the most important techniques in data mining. New algorithms must be developed in order to apply it to more areas. This paper proposes association rule algorithms for logical equality relationships, modified from the original Apriori and FP-Growth algorithms. Logical equality is defined as truerarrtrue (1rarr1) or falserarrfalse (0rarr0) associations. This special relationship commonly occurs in the real world, such as the linkage in the stock markets and customer loyalty for a certain product.
Keywords :
data mining; association rule algorithms; customer loyalty; data mining; logical equality relationships; stock markets; Algorithms; Apriori Algorithm; Association Rule; FP-Growth Algorithm; Negative Association Rule;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Information Technology Workshops, 2008. CIT Workshops 2008. IEEE 8th International Conference on
Conference_Location :
Sydney, QLD
Print_ISBN :
978-0-7695-3242-4
Electronic_ISBN :
978-0-7695-3239-1
Type :
conf
DOI :
10.1109/CIT.2008.Workshops.116
Filename :
4568474
Link To Document :
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