Memetic Algorithms for Ontology Alignment
Born primarily as means to model knowledge, ontologies have successfully been exploited to enable knowledge exchange among people, organizations and software agents. However, because of strong subjectivity of ontology modeling, a matching process is necessary in order to lead ontologies into mutual agreement and obtain the relative alignment, i.e., the set of correspondences among them. The topic of this presentation is to propose the application of an emergent class of evolutionary
algorithms, named Memetic Algorithms, to perform an automatic matching process. As shown in the performed experiments, the memetic approaches result suitable for solving ontology alignment problem.