Publication
Title
Axiomatization of frequent itemsets
Author
Abstract
Mining association rules is very popular in the data mining community. Most algorithms designed for finding association rules start with searching for frequent itemsets. Typically, in these algorithms, counting phases and pruning phases are interleaved. In the counting phase, partial information about the frequencies of selected itentsets is gathered. In the pruning phase as much as possible of the search space is pruned, based on the counting information. We introduce frequent set expressions to represent (possible partial) information acquired in the counting phase. A frequent set expression is a pair containing an itemset and a fraction that is a lower bound on the actual frequency of the itemset. A system of frequent sets is a collection of such pairs. We give an axiomatization for those systems that are complete in the sense that they explicitly contain all information they logically imply. Every system of frequent sets has a unique completion that actually represents all knowledge that can be derived. We also study sparse systems, in which not for every frequent set an expression is given. Furthermore, we explore the links with probabilistic logics. (C) 2002 Elsevier Science B.V. All rights reserved.
Language
English
Source (journal)
Theoretical computer science. - Amsterdam
Publication
Amsterdam : 2003
ISSN
0304-3975
Volume/pages
290:1(2003), p. 669-693
Article Reference
PII S0304-3975(02)00081-6
ISI
000179191000021
Medium
E-only publicatie
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 08.10.2008
Last edited 05.09.2017
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