Recently ontology mapping has been identified as a key issue in semantic-based technologies. A mapping algorithm aims at finding correspondences, and matching, between URIrefs (classes, relationships, instances) of a source ontology and a target ontology by combining several matching components (matchers) each of which relies on one or more ontology features (linguistic, structural, etc.). In this paper we propose an approach to ontology mapping based on the Lucene search engine library. We exploit Lucene features to build an index from a source ontology in which Lucene documents, gathering different kinds of information (name, value, comment, label, etc.) about URIrefs, are stored. Therefore mappings are derived by using values of the URIrefs of the target ontology as search arguments against the index created from the source ontology. Experimental results show the suitability of this approach in terms of Precision, Recall, F-Measure and execution time, as compared to other four approaches.