Association Rule Algorithms for Logical Equality Relationships

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. L...

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Bibliographic Details
Published inProceedings : 8th IEEE International Conference on Computer and Information Technology Workshops ; CIT Workshops 2008 : 8-11 July 2008, Sydney, Australia pp. 26 - 30
Main Authors Chyuan-Meei Chen, Shu-Hsien Liao
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2008
Subjects
Algorithms
Apriori Algorithm
Association Rule
Association rules
Banking
Communication industry
Conferences
Couplings
Data mining
FP-Growth Algorithm
Information technology
Itemsets
Logic circuits
Negative Association Rule
Stock markets
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Summary: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.
ISBN:076953242X
9780769532424
DOI:10.1109/CIT.2008.Workshops.116