HAL : hal-00363015, version 1

DOI : 10.1007/s10844-005-0266-z

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Journal of Intelligent Information Systems 24, 1 (2005) 29-60

Generating a condensed representation for association rules

Nicolas Pasquier (  Auteur correspondant ) 1, Rafik Taouil 2, Yves Bastide 3, Gerd Stumme 4, Lotfi Lakhal 5

(17/02/2005)

Association rule extraction from operational datasets often produces several tens of thousands, and even millions, of association rules. Moreover, many of these rules are redundant and thus useless. Using a semantic based on the closure of the Galois connection, we define a condensed representation for association rules. This representation is characterized by frequent closed itemsets and their generators. It contains the non-redundant association rules having minimal antecedent and maximal consequent, called min-max association rules. We think that these rules are the most relevant since they are the most general non-redundant association rules. Furthermore, this representation is a basis, i.e., a generating set for all association rules, their supports and their confidences, and all of them can be retrieved needless accessing the data. We introduce algorithms for extracting this basis and for reconstructing all association rules. Results of experiments carried out on real datasets show the usefulness of this approach. In order to generate this basis when an algorithm for extracting frequent itemsets—such as Apriori for instance—is used, we also present an algorithm for deriving frequent closed itemsets and their generators from frequent itemsets without using the dataset.

1 :	Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S)
	Université Nice Sophia Antipolis [UNS] – CNRS : UMR7271
2 :	LI - Université Francois Rabelais de Tours
	Université François Rabelais - Tours
3 :	Laboratoire d'Informatique, de Modélisation et d'optimisation des Systèmes (LIMOS)
	CNRS : UMR6158 – Université d'Auvergne - Clermont-Ferrand I – Université Blaise Pascal - Clermont-Ferrand II – Institut Français de Mécanique Avancée
4 :	Universitat Karlsruhe (UNIV K)
	Botanisches Institut I,
5 :	Laboratoire d'informatique Fondamentale de Marseille (LIF)
	CNRS : UMR6166 – Université de la Méditerranée - Aix-Marseille II – Université de Provence - Aix-Marseille I

Domaine

:

Informatique/Algorithme et structure de données Informatique/Base de données Informatique/Autre

Mots Clés : Data Mining – Algorithms – Lattices – Frequent Closed Itemsets – Association Rules

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Contributeur : Nicolas Pasquier <>

Soumis le : Lundi 26 Avril 2010, 12:35:58

Dernière modification le : Lundi 26 Avril 2010, 13:29:53