Ontology, which is regularly used in computer information retrieval and other computer applications, plays an essential role in effectively retrieving the concepts that have highly semantic similarity with the original query concept. Meanwhile, ontology also returns the results to the user. Ontology mapping is used to connect the relationship between different ontologies, and similarity computation is the essence of such applications. In this article, we present a ranking based ontology optimizing algorithm to get the ontology score function which map each ontology vertex to a real number, and the similarity between ontology vertices is determined according to the difference of the scores. The ontology framework is designed relied on the eigenpair computation, and the solution is obtained by means of operator calculation. The result data of simulation experiment implies that our new ontology method has high efficiency and accuracy in ontology similarity measure and ontology mapping in multiple disciplines.
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