The popularity of Ontology favored the appearance of several Ontologies to the same domain, thereby increasing the need of alignment techniques. In scenarios where ontologies comprising instances, the knowledge embedded in these instances can be useful to improve alignment. This paper extends a hybrid evolutionary approach, which applies a local optimization method, by taking instances into account in order to reduce premature convergence and, consequently, improve the quality of the resulting ontology alignment.
['Alex Alves', 'Kate Revoredo', 'Fernanda Araujo Baião']
Ontology alignment based on instances using hybrid genetic algorithm