Summary
In this contribution, a new Inductive Query by Example process is proposed to automatically derive extended Boolean queries for fuzzy information retrieval systems from a set of relevant documents provided by a user. The novelty of our approach is that it is able to simultanously generate several queries with a different precision-recall tradeoff in a single run. To do so, it is based on an advanced. evolutionary algorithm, GA-P, specially designed to tackle with multiobjective problems by means of a Pareto-based multiobjective technique. The performance of the new proposal will be tested on the usual Cranfield collection and compared to the well-known Kraft et al.’s process.
This work has been supported by CICYT under Project TIC2002–03276 and by the University of Granada under Project “Mejora de Metaheurísticas mediante Hibridación y sus Aplicaciones”.
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Cordón, O., Moya, F., Zarco, C. (2004). Automatic Learning of Multiple Extended Boolean Queries by Multiobjective GA-P Algorithms. In: Loia, V., Nikravesh, M., Zadeh, L.A. (eds) Fuzzy Logic and the Internet. Studies in Fuzziness and Soft Computing, vol 137. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39988-9_3
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DOI: https://doi.org/10.1007/978-3-540-39988-9_3
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