本文将汉语隐喻分类计算模型的研究引入汉语的机器理解当中,通过对大规模汉语隐喻语料的研究分析,结合汉语隐喻的认知特征,笔者构建了一套基于理解的汉语隐喻分类体系。分类主要以汉语隐喻句中本体和喻体的内在相似性作为切入点,从隐喻理解的方式、理解的难易程度以及理解所涉及的相关知识结构等方面进行综合分析,同时,辅以真实语料的统计分析,对分类的合理性作出了验证和修订,最终给出了基于理解的汉语隐喻分类体系,并对该体系作出了语言学上的比较和解释。

This paper introduces computational model of Chinese metaphor in machine-understanding of Chinese. By analyzing large-scale Chinese metaphor samples , we have classified Chinese metaphor based on understanding. The cognitive features of Chinese metaphor are also considered to improve our classification. The classification focuses on the similarity of the tenor and vehicle in a metaphor , showing the mode and difficulty of metaphor understanding. The relevant knowledge in metaphor understanding is also discussed. The classification is statistically verified. What's more , a program is developed to validate the rationality of our classification. Finally , a system of understanding-based classification of Chinese metaphor has been put forward. A comparison with other classification is listed. And a linguistic explaining of the system is given at the end of the paper.