{"title":"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","authors":"Y. Zu","doi":"10.1109/ECICE55674.2022.10042881","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Chinese-English Hybrid Rhetorical Question Recognition Model and Corpus Construction of Intelligent Web Text\",\"authors\":\"Y. Zu\",\"doi\":\"10.1109/ECICE55674.2022.10042881\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":282635,\"journal\":{\"name\":\"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECICE55674.2022.10042881\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECICE55674.2022.10042881","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.