【摘 要】
：
Nowadays,research on stylistic features(SF)mainly focuses on two aspects: lexical elements and syntactic structures.The lexical elements act as the content of a sentence and the syntactic structures c
【机 构】
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Tsinghua University,Beijing,China
【出 处】
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第十七届全国计算语言学学术会议暨第六届基于自然标注大数据的自然语言处理国际学术研讨会(CCL 2018)
论文部分内容阅读
Nowadays,research on stylistic features(SF)mainly focuses on two aspects: lexical elements and syntactic structures.The lexical elements act as the content of a sentence and the syntactic structures constitute the framework of a sentence.How to combine both aspects and exploit their common advantages is a challenging issue.In this paper,we propose a Principal Stylistic Features Analysis method(PSFA)to combine these two parts,and then mine the relations between features.From a statistical analysis point of view,many interesting linguistic phenomena can be found.Through the PSFA method,we finally extract some representative features which cover different aspects of styles.To verify the performance of these selected features,classification experiments are conducted.The results show that the elements selected by the PSFA method provide a significantly higher classification accuracy than other advanced methods.
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