Mining Bases for Association Rules Using Closed Sets
Published 24 August 2005
Rafik Taouil, N. Pasquier, Yves Bastide, Lotfi Lakhal
Citations43
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
Using the frequent closed itemset groundwork, this work proposes to generate bases for association rules, that are non-redundant generating sets for all association rules.
Abstract
We address the problem of the usefulness and the relevance of the set of discovered association rules. Using the frequent closed itemset groundwork, we propose to generate bases for association rules, that are non-redundant generating sets for all association rules.
Keywords
Computer Science
Formal Concept Analysis: Mathematical Foundations
4,282 Citations1998Bernhard Ganter, Rudolf Wille +1 more
Formal Concept Analysis
3,078 Citations1999Bernhard Ganter, Rudolf Wille
Lecture notes in computer scienceDiscovering Frequent Closed Itemsets for Association Rules
1,361 Citations1999Nicolas Pasquier, Yves Bastide +2 more
This paper proposes a new algorithm, called A-Close, using a closure mechanism to find frequent closed itemsets, and shows that this approach is very valuable for dense and/or correlated data that represent an important part of existing databases.
Information SystemsEfficient mining of association rules using closed itemset lattices
739 Citations1999Nicolas Pasquier, Yves Bastide +2 more
Experiments showed that Close is very efficient for mining dense and/or correlated data such as census style data, and performs reasonably well for market basket style data.
French digital mathematics library (Numdam)Implications partielles dans un contexte
136 Citations1991Michael Luxenburger
