Building knowledge base of urban emergency events based on crowdsourcing of social media. (28th January 2016)

• Record Type: Journal Article
• Authors: Xu, Zheng; Zhang, Hui; Hu, Chuanping; Mei, Lin; Xuan, Junyu; Choo, Kim‐Kwang Raymond; Sugumaran, Vijayan; Zhu, Yiwei
• Other Names: Bellatreche Ladjel guestEditor.; Mohania Mukesh guestEditor.; Luo Xiangfeng guestEditor.; Liu Yunhuai guestEditor.; Li Qing guestEditor.
• Is Part Of: Concurrency and computation. Volume 28:Number 15(2016)
• Page Start: 4038
• Page End: 4052
• Publication Date: 2016-01-28
• Subjects: crowdsourcing -- emergency events -- social media -- knowledge base; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.3780
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: An emergency event is an unexceptional event that exceeds the capacity of normal resources and organization to cope and a situation that poses an immediate risk to health, life, property, or environment. Crowdsourcing connects unobtrusive and ubiquitous sensing technologies, advanced data management and analytics models, and novel visualization methods, to create solutions that improve urban environment, human life quality, and city operation systems. The crowdsourcing on social media can be used to detect and analyze urban emergency events. In this paper, in order to detect and describe the real‐time urban emergency event, the knowledge base model is proposed. The crowdsourcing‐based knowledge base model is firstly introduced, which uses the information from social media. Secondly, the basic definition of the proposed knowledge base model including keywords, patterns, positive sentences, and knowledge graph is given. Thirdly, the temporal information is added to the proposed knowledge base model. The case study on real data sets shows that the proposed algorithm has good performance and high effectiveness in the analysis and detection of emergency events. Copyright © 2016 John Wiley & Sons, Ltd.