Improving metaheuristics convergence properties in inductive query by example using two strategies for reducing the search space

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.cor.2005.05.001 Byline: Sancho Salcedo-Sanz (a), Jing Su (b) Abstract: In this paper we present two strategies for reducing the time of convergence of two metaheuristics (genetic algorithms and simulated annealing) in inductive query by example (IQBE), which is a process for assisting the users of a given information retrieval system in the formulation of queries. Both strategies are based on a reduction of the search space size of the metaheuristics. The first strategy that we introduce is a compression-expansion strategy, where the terms are arranged into sets of a given size. The second strategy we consider is the so-called restricted search, where the number of terms in the genetic algorithm and simulated annealing encodings is fixed to be a given number m. We describe the implementation of the strategies and analyze when they can be successful, and the main drawbacks associated with them. Author Affiliation: (a) Sancho Salcedo-Sanz, Departamento de Teoria de la SeA[+ or -]al y Comunicaciones,Universidad de Alcala, Campus Universitario Carretera Madrid-Barcelona, km. 33, 28871 Alcala de Henares, Madrid, Spain (b) School of Computer Science, The University of Birmingham, B15 2TT, Edgbaston, Birmingham, UK