Sensing Urban Transportation Events from Multi-Channel Social Signals with the Word2vec Fusion Model

doi:10.3390/s18124093

	Sensing Urban Transportation Events from Multi-Channel Social Signals with the Word2vec Fusion Model
	Lu, Hao1,2 ; Shi, Kaize 1; Zhu, Yifan 1; Lv, Yisheng2 ; Niu, Zhendong 1
发表期刊	SENSORS
ISSN	1424-8220
	2018-12-01
卷号	18 期号:12 页码:22
通讯作者	Lv, Yisheng(yisheng.lv@ia.ac.cn) ; Niu, Zhendong(zniu@bit.edu.cn)
摘要	Social sensors perceive the real world through social media and online web services, which have the advantages of low cost and large coverage over traditional physical sensors. In intelligent transportation researches, sensing and analyzing such social signals provide a new path to monitor, control and optimize transportation systems. However, current research is largely focused on using single channel online social signals to extract and sense traffic information. Clearly, sensing and exploiting multi-channel social signals could effectively provide deeper understanding of traffic incidents. In this paper, we utilize cross-platform online data, i.e., Sina Weibo and News, as multi-channel social signals, then we propose a word2vec-based event fusion (WBEF) model for sensing, detecting, representing, linking and fusing urban traffic incidents. Thus, each traffic incident can be comprehensively described from multiple aspects, and finally the whole picture of unban traffic events can be obtained and visualized. The proposed WBEF architecture was trained by about 1.15 million multi-channel online data from Qingdao (a coastal city in China), and the experiments show our method surpasses the baseline model, achieving an 88.1% F-1 score in urban traffic incident detection. The model also demonstrates its effectiveness in the open scenario test.
关键词	intelligent sensors social transportation multi-channel signals event detection word2vec-based event fusion
DOI	10.3390/s18124093
关键词[WOS]	SENTIMENT ANALYSIS ; TRAFFIC CONGESTION ; TWITTER ; SYSTEMS ; MEDIA ; WEB
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61233001] ; National Natural Science Foundation of China[61773381] ; National Natural Science Foundation of China[61370137] ; Ministry of Education-China Mobile Research Foundation[2016/2-7] ; National Natural Science Foundation of China[61233001] ; National Natural Science Foundation of China[61773381] ; National Natural Science Foundation of China[61370137] ; Ministry of Education-China Mobile Research Foundation[2016/2-7]
项目资助者	National Natural Science Foundation of China ; Ministry of Education-China Mobile Research Foundation
WOS研究方向	Chemistry ; Electrochemistry ; Instruments & Instrumentation
WOS类目	Chemistry, Analytical ; Electrochemistry ; Instruments & Instrumentation
WOS记录号	WOS:000454817100012
出版者	MDPI
引用统计	被引频次：15[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/173211/25306
专题	复杂系统管理与控制国家重点实验室
通讯作者	Lv, Yisheng; Niu, Zhendong
作者单位	1.Beijing Inst Technol, Sch Comp Sci & Technol, Beijing 100081, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Lu, Hao,Shi, Kaize,Zhu, Yifan,et al. Sensing Urban Transportation Events from Multi-Channel Social Signals with the Word2vec Fusion Model[J]. SENSORS,2018,18(12):22.
APA	Lu, Hao,Shi, Kaize,Zhu, Yifan,Lv, Yisheng,&Niu, Zhendong.(2018).Sensing Urban Transportation Events from Multi-Channel Social Signals with the Word2vec Fusion Model.SENSORS,18(12),22.
MLA	Lu, Hao,et al."Sensing Urban Transportation Events from Multi-Channel Social Signals with the Word2vec Fusion Model".SENSORS 18.12(2018):22.