Multiple Knowledge-Enhanced Meteorological Social Briefing Generation

doi:10.1109/TCSS.2023.3298252

CORC > 自动化研究所 > 中国科学院自动化研究所 > 多模态人工智能系统全国重点实验室

	Multiple Knowledge-Enhanced Meteorological Social Briefing Generation
	Shi, Kaize 4,5; Peng, Xueping ; Lu, Hao 1,6; Zhu, Yifan 3; Niu, Zhendong 2,4
刊名	IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
	2023-08-03
页码	12
关键词	Controllable text generation decision support service emergency management meteorological social briefing natural disaster social weather
ISSN号	2329-924X
DOI	10.1109/TCSS.2023.3298252
通讯作者	Niu, Zhendong(zniu@bit.edu.cn)
英文摘要	Frequent meteorological disasters present new challenges for decision-making in disaster response. As a timely and effective source of intelligent information, social media plays a vital role in detecting and monitoring these situations. Meteorological social briefings summarize valuable information from numerous social media posts, providing essential decision-support services. This article proposes a multi-knowledge-enhanced summarization (MKES) model for automatically generating meteorological social briefing content from multiple Sina Weibo posts. The MKES model consists of a summary generation module and a knowledge enhancement module. The knowledge enhancement module guides and constrains the summary generation process using meteorological events and geographical location knowledge, resulting in summaries that focus on describing specific knowledge from the source text. The MKES model outperforms baseline models in content evaluation, as measured by ROUGE-1, ROUGE-2, and ROUGE-L scores, and in sentiment evaluation, as measured by F1 scores. Based on the MKES model, a framework for generating meteorological social briefings is developed, providing decision support services for the China Meteorological Administration (CMA).
资助项目	National Natural Science Foundation of China[62272048] ; National Key Research and Development Program of China[2019YFB1406302]
WOS研究方向	Computer Science
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:001043270800001
资助机构	National Natural Science Foundation of China ; National Key Research and Development Program of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/54005]
专题	多模态人工智能系统全国重点实验室
通讯作者	Niu, Zhendong
作者单位	1.Chinese Acad Sci, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China 2.Univ Pittsburgh, Sch Comp & Informat, Pittsburgh, PA 15260 USA 3.Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China 4.Beijing Inst Technol, Sch Comp Sci & Technol, Beijing 100081, Peoples R China 5.Univ Technol Sydney, Australian Artificial Intelligence Inst, Sydney, NSW 2007, Australia 6.Chinese Acad Sci, State Key Lab Management & Controlof Complex Syst, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Shi, Kaize,Peng, Xueping,Lu, Hao,et al. Multiple Knowledge-Enhanced Meteorological Social Briefing Generation[J]. IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,2023:12.
APA	Shi, Kaize,Peng, Xueping,Lu, Hao,Zhu, Yifan,&Niu, Zhendong.(2023).Multiple Knowledge-Enhanced Meteorological Social Briefing Generation.IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,12.
MLA	Shi, Kaize,et al."Multiple Knowledge-Enhanced Meteorological Social Briefing Generation".IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS (2023):12.