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Optimizing Ontology Alignment through Improved NSGA-II
Discrete Dynamics in Nature and Society
Over the past decades, a large number of complex optimization problems have been widely addressed through multiobjective evolutionary algorithms (MOEAs), and the knee solutions of the Pareto front (PF) are most likely to be fitting for the decision maker (DM) without any user preferences. This work investigates the ontology matching problem, which is a challenge in the semantic web (SW) domain. Due to the complex heterogeneity between two different ontologies, it is arduous to get an excellentdoi:10.1155/2020/8586058 fatcat:6hiq5zj2yfbahmfj5lzijedyci