How to find frequent patterns?

Wim Pijls and W.A. Koster

No EI 2005-24, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

Abstract: An improved version of DF, the depth-first implementation of Apriori, is presented. Given a database of (e.g., supermarket) transactions, the DF algorithm builds a so-called trie that contains all frequent itemsets, i.e., all itemsets that are contained in at least `minsup' transactions with `minsup' a given threshold value. In the trie, there is a one-to-one correspondence between the paths and the frequent itemsets. The new version, called DF+, differs from DF in that its data structure representing the database is borrowed from the FP-growth algorithm. So it combines the compact FP-growth data structure with the efficient trie-building method in DF.

Date: 2005-06-01
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