Wide-grained capsule network with sentence-level feature to detect meteorological event in social network

doi:10.1016/j.future.2019.08.013

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室

	Wide-grained capsule network with sentence-level feature to detect meteorological event in social network
	Shi, Kaize 2; Gong, Changjin 2; Lu, Hao 2,3; Zhu, Yifan 2; Niu, Zhendong 1,2
刊名	FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
	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.
资助项目	National Natural Science Foundation of China[61370137] ; Ministry of Education-China Mobile Research Foundation Project[2016/2-7]
WOS关键词	OPINION ; SYSTEM
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000501936300026
资助机构	National Natural Science Foundation of China ; Ministry of Education-China Mobile Research Foundation Project
内容类型	期刊论文
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.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
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.