基于动态分类的隐喻识别方法

隐喻计算是自然语言处理领域中的重要问题.尝试以差异性计算为基础，结合语言、心理和认知的角度对英语隐喻识别进行深入分析和探索.对人类而言，隐喻识别是一个动态分类的过程，动态分类是从多个角度来度量事物之间的差异性.研究了如何模仿人类来获取概念的特征、选择分类角度、在特定分类角度下计算差异性，并进行了英语名词性隐喻识别的实验.该方法对隐喻/常规表达识别的准确率达到85.4%，实验结果表明，该方法是有效的.

Method of Metaphor Recognition Based on Dynamic Categorization

Metaphor computation is an important problem of natural language processing. In this work, an intensive study of metaphor identification is carried out from different angles, including linguistical, psychological, and cognitive angles. Human categorization is a dynamic process of measuring difference between objects from different angles. Therefore, an idea about dynamic categorization is proposed from multiple angles to recognize metaphors, which is different from traditional metaphor recognition methods. The research involves three aspects:how to get features of concepts, how to choose angles by features, and how to measure difference based on a specific angle. Then, an experiment of nominal metaphor recognition is performed based on dynamic categorization. The experimental results show that the accuracy of metaphorical/literal references recognition can reach 85.4%. It supports the validity, efficiency of the proposed method.