Title :

Combining Evolutionary Algorithms and exact approaches for multi-objective knowledge discovery

Author(s) :

Khabzaoui, Mohammed [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Dhaenens, Clarisse [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Talbi, El-Ghazali [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]

Journal title :

RAIRO - Operations Research

Pages :

69-83

Publisher :

EDP Sciences

Publication date :

2008

ISSN :

0399-0559

English keyword(s) :

Hybridization
multi-objective optimization
knowledge discovery
association rules

HAL domain(s) :

Informatique [cs]/Recherche opérationnelle [cs.RO]

English abstract : [en]

An important task of knowledge discovery deals with discovering association rules. This very general model has been widely studied and efficient algorithms have been proposed. But most of the time, only frequent rules are ...
Show more >An important task of knowledge discovery deals with discovering association rules. This very general model has been widely studied and efficient algorithms have been proposed. But most of the time, only frequent rules are seeked. Here we propose to consider this problem as a multi-objective combinatorial optimization problem in order to be able to also find non frequent but interesting rules. As the search space may be very large, a discussion about different approaches is proposed and a hybrid approach that combines a metaheuristic and an exact operator is presented.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL