现代汉语隐喻句式自动识别研究

Q3 Social Sciences
Chunhong Li, Yongquan Li
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引用次数: 1

摘要

本文介绍了现代汉语隐喻句类型自动识别的研究进展。本文提出了一种基于CNN、RNN、Transform、Fast Text、Bert base等实验数据模型的对比识别实验设计方法。考虑到汉语隐喻句的特点,该方法适用于现代汉语隐喻句类型的自动识别,Bert库的准确率最高。本研究对汉语自然语言处理有重要贡献,可应用于自动作文纠错、文本分类、文本摘要、自动写作等领域。研究汉语文本信息和形式特征,以及人机交流的相关过程具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Automatic Recognition of Metaphorical Sentence Types in Modern Chinese
This paper presents work in progress towards automatic recognition of metaphorical sentence types in modern Chinese. We propose an approach to comparison recognition through the use of the experimental design, according to data sampling method, and the experimental data model of CNN, RNN, Transform, Fast Text, Bert base. Keeping in mind the characteristics of Chinese metaphorical sentence, the method is suitable and available for automatic recognition of metaphorical sentence types in modern Chinese, and the Bert base has the highest accuracy. This research contributes to Chinese natural language processing and can be applied in the fields of automatic composition correction, text classification, text summarization, automatic writing and so on. It is of great significance to Chinese text information and formal features, as well as the related process of human-computer communication.
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CiteScore
1.70
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0.00%
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