Wide-grained capsule network with sentence-level feature to detect meteorological event in social network
文献类型：期刊论文
| 作者 | Shi, Kaize2; Gong, Changjin2; Lu, Hao1,2 ; Zhu, Yifan2; Niu, Zhendong2,3
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| 刊名 | FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
 |
| 出版日期 | 2020 |
| 卷号 | 102页码:323-332 |
| 关键词 | Meteorological event detection Fine-tuned BERT Wide-grained capsule network SFMED model |
| ISSN号 | 0167-739X |
| DOI | 10.1016/j.future.2019.08.013 |
| 通讯作者 | Niu, Zhendong(zniu@bit.edu.cn) |
| 英文摘要 | In recent years, frequent meteorological disasters have caused great concern to people. It is particularly important to timely detect the meteorological events and release early warning information. Most traditional meteorological event detection methods rely on physical sensors, but such practice is usually costly and inflexible. As a new form of lightweight social sensor, social networks make up for the shortcomings of traditional physical sensors. In this paper, we propose a sentence-level feature based meteorological event detection model to detect 14 types of meteorological events defined by the China Meteorological Administration (CMA) in Sina Weibo. Our joint model consists of two modules: a fine-tuned BERT as the language model and a wide-grained capsule network as the event detection network. The design of our model considers the correlation among meteorological events and achieves the best results on all metrics compared with other baseline models. Moreover, as a practical application, our model has been applied to the meteorological event monitoring platform in the CMA Public Meteorological Service Center to provide online services. (C) 2019 Elsevier B.V. All rights reserved. |
| WOS关键词 | OPINION ; SYSTEM |
| 资助项目 | National Natural Science Foundation of China[61370137] ; Ministry of Education-China Mobile Research Foundation Project[2016/2-7] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000501936300026 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China ; Ministry of Education-China Mobile Research Foundation Project |
| 源URL | [http://ir.ia.ac.cn/handle/173211/29415]  |
| 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.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Beijing Inst Technol, Inst Software Intelligence & Software Engineer, Sch Comp Sci & Technol, Beijing 100081, Peoples R China 3.Univ Pittsburgh, Sch Comp & Informat, Pittsburgh, PA 15260 USA |
| 推荐引用方式 GB/T 7714 | Shi, Kaize,Gong, Changjin,Lu, Hao,et al. Wide-grained capsule network with sentence-level feature to detect meteorological event in social network[J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE,2020,102:323-332. |
| APA | Shi, Kaize,Gong, Changjin,Lu, Hao,Zhu, Yifan,&Niu, Zhendong.(2020).Wide-grained capsule network with sentence-level feature to detect meteorological event in social network.FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE,102,323-332. |
| MLA | Shi, Kaize,et al."Wide-grained capsule network with sentence-level feature to detect meteorological event in social network".FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 102(2020):323-332. |
入库方式： OAI收割
来源：自动化研究所
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