Template-Type: ReDIF-Paper 1.0
Author-Name: Pijls, W.H.L.M.
Author-Name-Last: Pijls
Author-Name-First: Wim
Author-Name: Kosters, W.A.
Author-Name-Last: Kosters
Author-Name-First: Walter A.
Title: Mining frequent itemsets a perspective from operations research
Abstract: Many papers on frequent itemsets have been published. Besides some
 contests in this field were held. In the majority of the papers the focus is
 on speed. Ad hoc algorithms and datastructures were introduced. In
 this paper we put most of the algorithms in one framework, using
 classical Operations Research paradigms such as backtracking, depth-first and
 breadth-first search, and branch-and-bound. Moreover we present
 experimental results where the different algorithms are implemented
 under similar designs.
Creation-Date: 2008-11-10
File-URL: https://repub.eur.nl/pub/13776/Report%20Ectrie%202008-24.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI 2008-24
Keywords: Frequent itemsets, data mining, operation research
Handle: RePEc:ems:eureir:13776