汉英混合反问句识别模型及智能网络文本语料库构建研究

Y. Zu
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引用次数: 0

摘要

随着英语在中国的普及,中英混合反问句在中国已经成为一种常见的表达方式。混合汉英反问句具有丰富的情感色彩,如果能够正确识别,可以改善情感分析和其他任务的结果。采用半监督学习和主动学习相结合的方法,提出了一种半自动收集修辞语料库的方法来构建汉英网络文本修辞语料库。基于语料库,从语义特征、位置特征、句法路径特征等方面分析汉英混合反问句的特征,开展反问句识别实验。实验结果表明,利用在线文本构建的反问句语料库训练出了一个高性能的反问句识别模型,模型的准确率、查全率和F1值均高于90%。同时,实验结果验证了句法路径特征和位置特征在反问句识别中的有效性。
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 Chinese-English Hybrid Rhetorical Question Recognition Model and Corpus Construction of Intelligent Web Text
With the popularity of English in China, Chinese-English mixed rhetorical question has become a common expression in China. Mixed Chinese-English rhetorical questions have rich emotional overtones, and if they can be correctly identified, they improve the results of sentiment analysis and other tasks. Using semi-supervised learning and active learning methods, a semi-automatic collection of the rhetorical corpus is proposed to construct a Chinese-English rhetorical corpus of web text. Based on the corpus, the characteristics of Chinese-English mixed rhetorical questions are analyzed from the aspects of semantic features, positional features, and syntactic path features to carry out a rhetorical question recognition experiment. Experimental results show that the rhetorical question corpus constructed from online texts trains a rhetorical question recognition model with high performance, and the accuracy, recall, and F1 values of the model are higher than 90%. At the same time, the experimental results verify the effectiveness of syntactic path features and location features in identifying rhetorical questions.
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