Discrete particle swarm optimisation for ontology alignment
Information Sciences: an International Journal
A hybrid evolutionary approach for solving the ontology alignment problem
International Journal of Intelligent Systems
A genetic algorithms-based approach for optimizing similarity aggregation in ontology matching
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
Optimizing ontology alignment through Memetic Algorithm based on Partial Reference Alignment
Expert Systems with Applications: An International Journal
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In this paper a genetic algorithm-based optimization procedure for ontology matching problem is presented as a feature-matching process. First, from a global view, we model the problem of ontology matching as an optimization problem of a mapping between two compared ontologies, and every ontology has its associated feature sets. Second, as a powerful heuristic search strategy, genetic algorithm is employed for the ontology matching problem. Given a certain mapping as optimizing object for GA, fitness function is defined as a global similarity measure function between two ontologies based on feature sets. Finally, a set of experiments are conducted to analysis and evaluate the performance of GA in solving ontology matching problem.