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Building knowledge base of urban emergency events based on crowdsourcing of social media
Author(s) -
Xu Zheng,
Zhang Hui,
Hu Chuanping,
Mei Lin,
Xuan Junyu,
Choo KimKwang Raymond,
Sugumaran Vijayan,
Zhu Yiwei
Publication year - 2016
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.3780
Subject(s) - crowdsourcing , computer science , knowledge base , event (particle physics) , social media , analytics , data science , emergency management , graph , knowledge management , artificial intelligence , world wide web , physics , theoretical computer science , quantum mechanics , political science , law
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.