An Algorithm for Discovering Ontology Mappings in P2P Systems
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
LOM: a linguistic ontology matcher based on information retrieval
Journal of Information Science
Deriving Concept Mappings through Instance Mappings
ASWC '08 Proceedings of the 3rd Asian Semantic Web Conference on The Semantic Web
SECCO: On Building Semantic Links in Peer-to-Peer Networks
Journal on Data Semantics XII
A Knowledge Management System Using Bayesian Networks
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
UFOme: An ontology mapping system with strategy prediction capabilities
Data & Knowledge Engineering
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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.