Increasingly, ontologies are being developed and exposed on the Web to support a variety of applications, including biological knowledge sharing, enhanced search and discovery, and rapid enterprise integration. This explosion of knowledge sharing on the web is also leading to the formation of knowledge silos and a growing need for integration and enrichment of these sources. Automated solutions to mapping ontologies are emerging that address this growing need, with very promising results. However, nearly all approaches have focused on mapping ontologies using relationships of similarity and equivalence and very few have applied knowledge in upper ontologies. We present a set of algorithms to acquire relationships between ontological components beyond similarity and equivalence that include hyponymy and more importantly, algorithms to map ontologies based on relationships that are specified within the ontologies. These algorithms employ the semantics of OWL in conjunction with online linguistic resources and upper ontologies. We also present a performance comparison of two knowledge sources applied in the ontology mapping process; namely, WordNet and OpenCyc.
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