Ontology Alignment with Weightless Neural Networks

In this paper, we present an ontology matching process based on the usage of Weightless Neural Networks (WNN). The alignment of ontologies for specific domains provides several benefits, such as interoperability among different systems and the improvement of the domain knowledge derived from the insights inferred from the combined information contained in the various ontologies. A WiSARD classifier is built to estimate a distribution-based similarity measure among the concepts of the several ontologies being matched. To validate our approach, we apply the proposed matching process to the knowledge domain of algorithms, software and computational problems, having some promising results.