Automatic generation of meteorological briefing by event knowledge guided summarization model

doi:10.1016/j.knosys.2019.105379

	Automatic generation of meteorological briefing by event knowledge guided summarization model
	Shi, Kaize 1; Lu, Hao1,3 ; Zhu, Yifan 1; Niu, Zhendong 1,2,4
发表期刊	KNOWLEDGE-BASED SYSTEMS
ISSN	0950-7051
	2020-03-15
卷号	192 页码:14
通讯作者	Niu, Zhendong(zniu@bit.edu.cn)
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.
关键词	Meteorological domain Fine-tuned BERT model Event knowledge guided summarization EKGS model Briefing generation framework Meteorological decision support platform
DOI	10.1016/j.knosys.2019.105379
关键词[WOS]	SOCIAL MEDIA ; ENSO ; NETWORK ; TEXT
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61370137] ; Ministry of Education of China - China Mobile Research Foundation Project[2016/2-7]
项目资助者	National Natural Science Foundation of China ; Ministry of Education of China - China Mobile Research Foundation Project
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000519335400038
出版者	ELSEVIER
引用统计	被引频次：12[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/38624
专题	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.Beijing Inst Technol, Inst Software Intelligence & Software Engineer, Sch Comp Sci & Technol, Beijing 100081, Peoples R China 2.Beijing Engn Res Ctr Mass Language Informat Proc, Beijing 100081, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 4.Univ Pittsburgh, Sch Comp & Informat, Pittsburgh, PA 15260 USA
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.