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

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.