https://scholars.lib.ntu.edu.tw/handle/123456789/632516
標題: | Learning to generate news headlines with media's stance | 作者: | Lin T Chu J Huang H.-H HSIN-HSI CHEN |
公開日期: | 2020 | 起(迄)頁: | 554-559 | 來源出版物: | Proceedings - 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2020 | 摘要: | News headline generation can be viewed as a subtask of summarization. When it comes to news headlines or their source articles, positions and stances are usually the main concern for both the publisher and the readers. However, this aspect of headlines is rarely explored along with the developed headline generators. In this paper, we initiate a headline generation task considering the stance for a specific party. We extend the base model with different ways to include stances and investigate their pros and cons. We also propose approaches to evaluate the performance of handling stances. Finally, we come up with an ensemble model to cope with generation quality and stance consideration at the same time, whose results are comparable to human-written headlines. © 2020 IEEE. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114423509&doi=10.1109%2fWIIAT50758.2020.00083&partnerID=40&md5=ee33d6a11ff634864a702b0255cb8455 https://scholars.lib.ntu.edu.tw/handle/123456789/632516 |
DOI: | 10.1109/WIIAT50758.2020.00083 | SDG/關鍵字: | Base models; Ensemble modeling; Headline generation; Subtask; Intelligent agents |
顯示於: | 資訊工程學系 |
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