An Approach to Chinese Metaphor Identification Based on Word Abstractness
Huang Xiaoxi1,2, Zhang Hua1, Lu Bei1, Wang Rongbo1, Wu Ting1
1 Institution of Cognitive and Intelligent Computing, Hangzhou Dianzi University, Hangzhou 310018, China;
2 Center for the Study of Language and Cognition, Zhejiang University, Hangzhou 310028, China
[Objective] Design a method to automatically compute Chinese word abstractness, and introduce it into metaphor identification task in natural language understanding. [Methods] The word abstractness is computed by logistic regression model. The features are the word vectors computed by neural network model and the feature weight vectors come from a hand coded abstractness dictionary. A metaphor identification algorithm based on word abstractness is proposed to demonstrate the validity of this method. [Results] By comparing with the existing methods of word abstractness computing, this method has better accordance with human cognition and is an effective method in metaphor identification task. [Limitations] The utilization of word vectors for word abstractness is defective. The scale of the abstract words affects the learning of feature weight vectors. [Conclusions] Word abstractness computing reflects the ability to concept classification, Chinese word abstractness computed by this method is better fitting the human cognition, and the experimental results show that word abstractness can improve the effect of metaphor identification.
黄孝喜, 张华, 陆蓓, 王荣波, 吴铤. 一种基于词语抽象度的汉语隐喻识别方法[J]. 现代图书情报技术, 2015, 31(4): 34-40.
Huang Xiaoxi, Zhang Hua, Lu Bei, Wang Rongbo, Wu Ting. An Approach to Chinese Metaphor Identification Based on Word Abstractness. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2015.04.05.
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