基于本体的概念间相似度计算已经在信息检索等诸多领域成为当今信息技术研究的热点问题之一。本文的工作是针对描述同一领域的多个本体间存在的异构问题，设计一种快速高效的映射算法来实现异构本体的融合。本文提出了一种基于异构本体的相似度计算方法，通过字面概念相似度和语义结构（包括节点深度、节点密度、边权重、信息量等）相似度等方面的综合计算，可以准确地得到异构本体间的概念映射关系；同时，通过对映射方法的优化，算法的匹配速度也有很大程度的提高。实验结果表明，该算法可以有效地排除本体异构的影响，得到较好的概念相似性计算效果

The research of ontologybased similarity calculation between concepts has already been a hot issue of information technology in the fields of information retrieval, and so on. In this paper, the contents of the study is to find a fast and efficient mapping algorithm for heterogeneous ontologies in the same field.This paper puts forward a method of similarity calculation based on heterogeneous ontologies,and the factors of similarity of literal meaning and semantic structure(including the depth of the node, node density, edge weight,information content, etc.) can get concept mapping between heterogeneous ontologies more accurately.Simultaneously,taking into account the optimization of mapping method,the speed of matching has also been improved to a large extent. The problem of how to improve the speed of matching more effectually has been mentioned in this paper.The experimental results show this method can effectively get better effectiveness with concept similarity computing, excluding the effects of heterogeneous ontologies.