Abstract
Ontology similarity calculation and ontology mapping are crucial research topics in information retrieval. Ontology, as a concept structure model, is also widely used in biology, physics, geography and social sciences. In this paper, we propose new algorithms for ontology similarity measurement and ontology mapping using supervised multidimensional scaling and multi-dividing technologies. Two experimental results show that the proposed new algorithm has high accuracy and efficiency on ontology similarity calculation and ontology mapping in certain applications.
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