Abstract
In information retrieval, ontology is used to search the information which has highly semantic similarity of the original query concept, and return the results to the user. Ontology mapping is used to create the relationship between different ontologies, and the essence of which is similarity computation. In this article, we present new algorithms for ontology similarity measure and ontology mapping by determining the similarity matrix of ontology. The optimisation strategy and iterative procedure are designed in terms of metric distance learning tricks. The simulation experimental results show that the proposed new algorithms have high accuracy and efficiency on ontology similarity measure and ontology mapping in biology, physics applications, plant science and humanoid robotics.
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