Abstract: The current computation models of Chinese semantic relevancy variate due to various definitions of relevancy degree.These models are almost based on a similarity computation model，which much limits its application.This paper presents a new definition of semantic relevancy，and defines two words semantically related if the two concepts associated with the two words respectively have the relationship in a semantic knowledge base like HowNet.By mining all the direct and indirect relationships，a new computation model of semantic relevancy is proposed.This model can be generalized to any semantic knowledge bases constructed by the knowledge dictionary mark-up language.Finally，it applies the computation model to the word sense disambiguation problem，and therefore validates that this computation model can be efficiently employed to many applications.

摘要： 现有的中文语义相关度计算模型对相关度的定义并不明确和统一，且计算方法多以相似度计算为基础，导致应用语义相关度存在局限。提出了一个新的语义相关的定义，认为两个词所表达的概念之间，如果存在用类似“知网”的知识描述体系所描述的语义关系，那么这两个概念之间就是语义相关的。通过挖掘这些直接或间接的关系，提出了一种新的语义相关度的计算模型，适用于所有类似知网的知识体系中语义相关度的计算。最后将该计算模型应用于词义排歧，验证了该计算模型的有效性。