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Sarcasm expression is a pervasive literary technique in which people intentionally express the opposite of what is implied. Accurate detection of sarcasm in a text can facilitate the understanding of speakers’ true intentions and promote other natural language processing tasks, especially sentiment analysis tasks. Since sarcasm is a kind of implicit sentiment expression and speakers deliberately confuse the audience, it is challenging to detect sarcasm only by text. Existing approaches based on machine learning and deep learning achieved unsatisfactory performance when handling sarcasm text with complex expression or needing specific background knowledge to understand. Especially, due to the characteristics of the Chinese language itself, sarcasm detection in Chinese is more difficult. To alleviate this dilemma on Chinese sarcasm detection, we propose a sememe and auxiliary enhanced attention neural model, SAAG. At the word level, we introduce sememe knowledge to enhance the representation learning of Chinese words. Sememe is the minimum unit of meaning, which is a fine-grained portrayal of a word. At the sentence level, we leverage some auxiliary information, such as the news title, to learning the representation of the context and background of sarcasm expression. Then, we construct the representation of text expression progressively and dynamically. The evaluation on a sarcasm dateset, consisting of comments on news text, reveals that our proposed approach is effective and outperforms the state-of-the-art models.  相似文献   
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表现主义兴起于20世纪初,盛行于20、30年代的德、美、北欧等国。奥地利小说家卡夫卡是这个流派的杰出代表,其小说的表现主义技巧达到了运用自如、登峰造极的境界,卡夫卡的小说寓荒诞于真实,融幻想与怪诞于一体。他所创造的艺术世界.人称“卡夫卡式”,如同“莎士比亚化”一样.也是内容和形式的有机统一体.并已成为世界文学史上的一个美学概念。  相似文献   
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反讽渗透于奥斯丁小说的每一个层面,从语言、人物、场景到更深层的主题和构思,它不仅成为奥斯丁作品的一种主要艺术手段,而且还成为臭斯丁领悟世界的一种方式。本文结合其反讽在语言、人物、场景、主题等各个层面的表现,更为全面和深入地探讨奥斯丁的反讽艺术。  相似文献   
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