计算机科学 ›› 2016, Vol. 43 ›› Issue (5): 209-213.doi: 10.11896/j.issn.1002-137X.2016.05.038

• 人工智能 • 上一篇    下一篇

基于社交网络群智感知信息的非常规突发事件描述方法研究

陈海燕,徐峥   

  1. 华东政法大学计算机科学与技术系 上海201620,公安部第三研究所物联网中心 上海201142;清华大学公共安全研究院 北京100084
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家社会科学基金项目(06BFX051),国家自然科学基金青年项目(6130202),上海高校选拔培养优秀青年教师科研专项基金(hzf05046),上海市自然科学基金青年项目(13ZR1452900),中国博士后基金一等面上项目(2014M560085)资助

Crowdsourcing Based Description of Urban Emergency Events

CHEN Hai-yan and XU Zheng   

  • Online:2018-12-01 Published:2018-12-01

摘要: 群智感知是以近年来兴起的物联网、大数据、云计算等多种技术为基础发展起来的。群智感知就是用城市环境中感知的大数据来解决城市本身所面临的挑战,通过对多源异构数据的整合、分析和挖掘来提取知识和价值,从而提高城市服务的现代化水平。非常规突发事件是一类前兆特征不充分、具有明显的复杂性和潜在次生衍生危害、破坏性严重、采用传统管理方式难以应对处置的罕见重大突发事件。由于构成群智感知网络的基本单元是无所不在的移动智能终端用户,这种新型的体系架构无论是在感知及认知的广度、深度还是在构建的成本与速度上,都是传统技术手段所无法比拟的。对社交网络信息进行语义感知、时空关联等以对非常规突发事件进行描述,并通过实例对该方法进行验证。非常规突发事件的语义信息包括关键词、模式、语句等。时空信息用来描述非常规突发事件的客观时间属性与空间属性。时间属性包括非常规突发事件的发生时间、结束时间,以及重要时间点。空间属性包括非常规突发事件的发生位置、影响位置,位置信息可以是路名建筑物名称,也可以具体到GIS信息。多媒体信息包括图像、视频、音频等。

关键词: 群智感知,非常规突发事件,语义描述,时空感知

Abstract: Crowdsourcing is a process of acquisition,integration,and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces,such as sensors,devices,vehicles,buildings,and human.Especially,nowadays,no countries,no communities,and no person are immune to urban emergency events.Detection about urban emergency events,e.g.,fires,storms,traffic jams,is of great importance to protect the security of humans.Recently,social media feeds are rapidly emerging as a novel platform for providing and dissemination of information that is often geographic.The content from social media often includes references to urban emergency events occurring at,or affecting specific locations.In this paper,in order to describe the real time urban emergency event,the crowdsourcing based model was proposed.Firstly,users of social media are set as the target of crowd-sourcing.Secondly,the semantic,spatial and temporal information from the social media are extracted to detect the real time event.Thirdly,a GIS based annotation of the detected urban emergency event is shown.The proposed method was evaluated with extensive case studies based on real urban emergency events.The results show the accuracy and efficiency of the proposed method.

Key words: Crowdsourcing,Urban emergency event,Semantic description,Spatial temporal

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