{"type":"ScholarlyArticle","title":"A Hierarchical End-to-End Model for Jointly Improving Text Summarization and Sentiment Classification","authors":[{"name":"Shuming Ma","slug":"shuming-ma","given":"Shuming","family":"Ma","affiliation":"MOE Key Lab of Computational Linguistics , School of EECS , Peking University"},{"name":"Xu Sun","slug":"xu-sun","given":"Xu","family":"Sun","affiliation":"MOE Key Lab of Computational Linguistics , School of EECS , Peking University"},{"name":"Junyang Lin","slug":"junyang-lin","given":"Junyang","family":"Lin","affiliation":"School of Foreign Languages , Peking University"},{"name":"Xuancheng Ren","slug":"xuancheng-ren","given":"Xuancheng","family":"Ren","affiliation":"MOE Key Lab of Computational Linguistics , School of EECS , Peking University"}],"abstract":"Text summarization and sentiment classification both aim to capture the main ideas of the text but at different levels. Text summarization is to describe the text within a few sentences, while sentiment classification can be regarded as a special type of summarization which ``summarizes'' the text into a even more abstract fashion, i.e., a sentiment class. Based on this idea, we propose a hierarchical end-to-end model for joint learning of text summarization and sentiment classification, where the sentiment classification label is treated as the further ``summarization'' of the text summarization output. Hence, the sentiment classification layer is put upon the text summarization layer, and a hierarchical structure is derived. Experimental results on Amazon online reviews datasets show that our model achieves better performance than the strong baseline systems on both abstractive summarization and sentiment classification.","doi":"10.24963/ijcai.2018/591","url":"https://ijcai.org/proceedings/2018/591","pdf":"https://ijcai.org/proceedings/2018/0591.pdf","markdown":"https://ijcai.org/proceedings/2018/591.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/591","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Natural Language Processing","track":"Main track","number":591,"pages":{"first":4251,"last":4257},"keywords":["Natural Language Processing: Sentiment Analysis and Text Mining","Natural Language Processing: Natural Language Summarization","Natural Language Processing: Text Classification","Natural Language Processing: Natural Language Processing"],"videos":[],"references":[{"position":1,"raw":"[Cao et al., 2017] Ziqiang Cao, Wenjie Li, Sujian Li, and Furu Wei. 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