@inproceedings{tai-etal-2021-yi,
    title = "汉语语体特征的计量与分类研究(A study on the measurement and classification of {C}hinese stylistic features)",
    author = "Tai, Qinqing  and
      Rao, Gaoqi",
    editor = "Li, Sheng  and
      Sun, Maosong  and
      Liu, Yang  and
      Wu, Hua  and
      Liu, Kang  and
      Che, Wanxiang  and
      He, Shizhu  and
      Rao, Gaoqi",
    booktitle = "Proceedings of the 20th Chinese National Conference on Computational Linguistics",
    month = aug,
    year = "2021",
    address = "Huhhot, China",
    publisher = "Chinese Information Processing Society of China",
    url = "https://preview.aclanthology.org/fix-sig-urls/2021.ccl-1.37/",
    pages = "398--412",
    language = "zho",
    abstract = "本文运用语料库和统计方法对汉语语体进行特征的计量研究,并进一步实现自动分类任务。首先通过单因素方差分析描述语体特征区别不同语体的作用和功能。其次,选取其中具有区分度的语言要素拟合逻辑回归模型,量化语体表达形式并观察特征对语体构成的重要性,并通过聚类计算得到了语体的范畴分类体系。最后,以具有代表性的机器学习模型为分类器,挖掘不同组合特征的结构对于语体自动分类的影响。得出在{``}词2n+词类2n+标点符号2n+语言特征{''}的组合特征上,取得了最好的分类结果,随机森林模型达到97.25{\%}的准确率。"
}