Combining evolutionary algorithms and exact approaches for multi-objective knowledge discovery
RAIRO - Operations Research - Recherche Opérationnelle, Volume 42 (2008) no. 1, pp. 69-83.

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.

DOI: 10.1051/ro:2008004
Classification: 90Cxx, 68XX
Keywords: hybridization, multi-objective optimization, knowledge discovery, association rules
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Khabzaoui, Mohammed; Dhaenens, Clarisse; Talbi, El-Ghazali. Combining evolutionary algorithms and exact approaches for multi-objective knowledge discovery. RAIRO - Operations Research - Recherche Opérationnelle, Volume 42 (2008) no. 1, pp. 69-83. doi : 10.1051/ro:2008004. http://archive.numdam.org/articles/10.1051/ro:2008004/

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