A new algorithm for automated ontology mapping based on linguistic similarity and structure similarity is presented. First, the concept of WordNet is turned into a vector, then the similarity of two entities is calculated according to the cosine of the angle between the corresponding vectors. Secondly, based on the linguistic similarity, a weighted function and a sigmoid function can be used to combine the linguistic similarity and structure similarity to compute the similarity of an ontology. Experimental results show that the matching ratio can reach 63% to 70% and it can effectively accomplish the mapping between ontologies.
