Association Rule Algorithms for Logical Equality Relationships

• Published in: Proceedings : 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
• Language: English
• 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
• DOI: 10.1109/CIT.2008.Workshops.116
• ISBN: 076953242X; 9780769532424

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.