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  • 标题:Automatic Genre Classification via N-grams of Part-of-Speech Tags
  • 本地全文:下载
  • 作者:Xiaoyan Tang ; Xiaoyan Tang ; Jing Cao
  • 期刊名称:Procedia - Social and Behavioral Sciences
  • 印刷版ISSN:1877-0428
  • 出版年度:2015
  • 卷号:198
  • 页码:474-478
  • DOI:10.1016/j.sbspro.2015.07.468
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractRecurring sequences of words have long been considered as a signifier of different genres and registers by corpus linguists. The previous research mainly focused on lexical n-grams. Nevertheless, n-grams of other linguistic features, such as part-of-speech, have been less studied. The current study is expected to examine whether n-grams of part-of-speech tags extracted from a large corpus can be a discriminator of different genres. The results show that a strong correlation exists between the information about n-grams of part-of-speech tags and the genre of the text.
  • 关键词:Automatic Genre Classification;BNC Baby;N-grams;Naïve Bayes Classifier;Multinomial Naïve Bayes Classifier;Part-of-Speech
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