Method for extracting association rules from transactions in...

Details Method for extracting association rules from transactions in... Method for extracting association rules from transactions in...

2008-05-06

2008-05-06

Wong, Don (Department: 2163)

Data processing: database and file management or data structures

Database design

Data structure types

C707S793000, C707S793000, C707S793000, C707S793000, C715S252000

Reexamination Certificate

active

07370033

ABSTRACT:
Apriori algorithms are popular data mining techniques for extracting association rules from a body of data. The computational complexity of these algorithms is reduced by representing itemset information at cells of a hypercube. The cells encode associations between the items of each transaction. Direct computation of a cell as a lexicographic combination of items accelerates the computation of itemsets, and thereby improves the computational runtime complexity of the apriori algorithm that discovers association rules. Even faster computation is achieved by a user selected cardinality that limits the maximum size of the itemsets.

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Charles Mifsud: “Algorithm 154: Combination in Lexicographical Order” Mar. 1963, Communication of the ACM, vol. 6, p. 103.

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