Ontology mapping using the method of particle swarm optimization

The paper is devoted to the integration of data from distributed heterogeneous information sources on the basis of ontology. The method of semantic similarity calculation between concepts allows to evaluate similarity between concepts. A technique for semantic similarity estimation between concepts of two ontologies is proposed. The main feature is the automatic calculation of weights using particle swarm optimization method. With the proposed approach, vectors of weights are generated. They correspond to different coefficients of semantic similarity. Then, using the obtained weights, the combination of different coefficients of semantic similarity is performed. Each concept from an ontology is attributed wit a set of relevant semantic concepts from another ontology. This allows to obtain sets of optimal and quasi-optimal solutions.