Evolutionary Learning of Boolean Queries by Multiobjective Genetic Programming

Authors:
Oscar Cordón;Enrique Herrera-Viedma;María Luque
Affiliations:
-;-;-
Venue:
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Year:
2002

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Abstract

The performance of an information retrieval system is usually measured in terms of two different criteria, precision and recall. This way, the optimization of any of its components is a clear example of a multiobjective problem. However, although evolutionary algorithms have been widely applied in the information retrieval area, in all of these applications both criteria have been combined in a single scalar fitness function by means of a weighting scheme. In this paper, we will tackle with a usual information retrieval problem, the automatic derivation of Boolean queries, by incorporating a well known Pareto-based multiobjective evolutionary approach, MOGA, into a previous proposal of a genetic programming technique for this task.