Automatic generation of meteorological briefing by event knowledge guided summarization model
Shi, Kaize2; Lu, Hao2,3; Zhu, Yifan2; Niu, Zhendong1,2,4
刊名KNOWLEDGE-BASED SYSTEMS
2020-03-15
卷号192页码:14
关键词Meteorological domain Fine-tuned BERT model Event knowledge guided summarization EKGS model Briefing generation framework Meteorological decision support platform
ISSN号0950-7051
DOI10.1016/j.knosys.2019.105379
通讯作者Niu, Zhendong(zniu@bit.edu.cn)
英文摘要In recent years, frequent meteorological disasters have brought great suffering to people. The meteorological briefing is an effective way to realize the real-time perception of extreme meteorological events, which is of great significance for decision-makers to formulate plans and provide timely assistance. Traditional meteorological briefings primarily rely on physical sensors for data collection and are organized manually. However, such an approach has the disadvantages of rigid content, high cost, and poor real-time performance. As an emerging lightweight social sensor, social networks can respond to real world events in a timely and comprehensive manner, which also makes up for the shortcomings of the traditional methods. In this paper, we present an event knowledge guided summarization (EKGS) model to automatically summarize weibo posts in the meteorological domain. Our model consists of two modules: a summary generation module and an event knowledge guidance module. The event knowledge guidance module is used to guide and constrain the content generated by the summary generation module, so that it can generate the content with core knowledge of specific events, which are 14 types of extreme meteorological events defined by the China Meteorological Administration (CMA). Compared to other baseline models, our EKGS model achieves the best test results on all metrics. In addition, we construct an automatic meteorological briefing generation framework based on the EKGS model, which has been applied as an online service to the meteorological briefing overview module of the CMA Public Meteorological Service Center. (C) 2019 Elsevier B.V. All rights reserved.
资助项目National Natural Science Foundation of China[61370137] ; Ministry of Education of China - China Mobile Research Foundation Project[2016/2-7]
WOS关键词SOCIAL MEDIA ; ENSO ; NETWORK ; TEXT
WOS研究方向Computer Science
语种英语
出版者ELSEVIER
WOS记录号WOS:000519335400038
资助机构National Natural Science Foundation of China ; Ministry of Education of China - China Mobile Research Foundation Project
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/38623]  
专题自动化研究所_复杂系统管理与控制国家重点实验室
通讯作者Niu, Zhendong
作者单位1.Univ Pittsburgh, Sch Comp & Informat, Pittsburgh, PA 15260 USA
2.Beijing Inst Technol, Inst Software Intelligence & Software Engineer, Sch Comp Sci & Technol, Beijing 100081, Peoples R China
3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
4.Beijing Engn Res Ctr Mass Language Informat Proc, Beijing 100081, Peoples R China
推荐引用方式
GB/T 7714
Shi, Kaize,Lu, Hao,Zhu, Yifan,et al. Automatic generation of meteorological briefing by event knowledge guided summarization model[J]. KNOWLEDGE-BASED SYSTEMS,2020,192:14.
APA Shi, Kaize,Lu, Hao,Zhu, Yifan,&Niu, Zhendong.(2020).Automatic generation of meteorological briefing by event knowledge guided summarization model.KNOWLEDGE-BASED SYSTEMS,192,14.
MLA Shi, Kaize,et al."Automatic generation of meteorological briefing by event knowledge guided summarization model".KNOWLEDGE-BASED SYSTEMS 192(2020):14.
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