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Automatic Narrative Humor Recognition Method Using Machine Learning and Semantic Similarity Based Punchline Detection

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タイトル: Automatic Narrative Humor Recognition Method Using Machine Learning and Semantic Similarity Based Punchline Detection
著者: Rafal, Rzepka 著作を一覧する
Yusuke, Amaya 著作を一覧する
Motoki, Yatsu 著作を一覧する
Kenji, Araki 著作を一覧する
発行日: 2015年 7月26日
出版者: IJCAI
誌名: International Workshop on Chance Discovery, Data Synthesis and Data Market in IJCAI2015
抄録: In this paper we introduce our method for recognizing jokes written in Japanese language by where the punchline is detected using WordNet. The results showed that when compared to method based on Bayesian posterior probability baseline, the pro- posed system achieved 5.3 point increase in recall and 2.6 point increase in classification accuracy. Our work1 is the first challenge to detect humor in Japanese language and this ability can be utilized not only for more natural reactions while perceiving user’s utterance, but also for discovering funny stories to be uttered by an agent.
資料タイプ: proceedings
URI: http://hdl.handle.net/2115/63638
出現コレクション:雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

提供者: Rafal Rzepka

 

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