Automatic generation of meteorological briefing by event knowledge guided summarization model
文献类型：期刊论文
| 作者 | Shi, Kaize1; Lu, Hao1,3 ; Zhu, Yifan1; Niu, Zhendong1,2,4
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| 刊名 | KNOWLEDGE-BASED SYSTEMS
 |
| 出版日期 | 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 |
| DOI | 10.1016/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. |
| WOS关键词 | SOCIAL MEDIA ; ENSO ; NETWORK ; TEXT |
| 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研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000519335400038 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China ; Ministry of Education of China - China Mobile Research Foundation Project |
| 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.Beijing Inst Technol, Inst Software Intelligence & Software Engineer, Sch Comp Sci & Technol, Beijing 100081, Peoples R China 2.Univ Pittsburgh, Sch Comp & Informat, Pittsburgh, PA 15260 USA 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. |
入库方式： OAI收割
来源：自动化研究所
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