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LBS大数据在大型聚集活动中的情报预警应用 被引量:9

The Application of LBS Big Data in the Intelligence Warning System of the Large Gathering Activities
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摘要 [目的/意义]大数据时代,如何有效监测大型聚集活动中人流、车流、客流、应急部署、网络舆情等实时LBS位置数据,并结合相关挖掘模型与算法快速做出研判与预警,已成为当今大型聚集活动中情报工作的研究热点。[方法/过程]在总结分析大型聚集活动情报预警工作的基础上,分析了LBS大数据的潜在价值,提炼了LBS大数据的显著特征,提出了利用LBS大数据搭建大型聚集活动突发事件应急情报体系中LBS大数据综合监测预警平台的构想。[结果/结论]从数据层、挖掘层、应用层三个层面剖析了该平台的组织架构及具体应用场景,揭示了LBS大数据在大型聚集活动中情报预警工作中的巨大潜力。 [ Purpose/Significance ] The intelligence work of the large gathering activities has focused on the application of LBS big data in the intelligence warning in the age of big data. LBS data can be collected to monitor the visitors flow, traffic flow, emergency arrangement and network public opinion using the model of data mining in the region of large gathering activities. [ Method/Process] The potential val- ue and marked feature of LBS data were investigated based on the analysis of the intelligence warning system of the large gathering activi- ties. The integrated monitoring platform based on LBS big data was put forward to afford assistant decision support functions for the intelli- gence warning system of the large gathering activities. [ Result/Condusion] The organization architecture and application scenarios of the integrated monitoring platform were indicated by the three levels including data layer, mining layer and application layer. LBS data has huge potential for the intelligence warning work of the large gathering activities.
出处 《情报杂志》 CSSCI 北大核心 2017年第7期28-33,51,共7页 Journal of Intelligence
基金 辽宁省社会科学规划基金项目"大型聚集活动拥挤踩踏事件中的情报信息工作机制研究"(编号:L15BTQ005)研究成果之一 中国刑事警察学院中央高校基本科研业务费重大项目培育计划项目"Hadoop架构下基于KNN文本分类算法的公安情报分析关键技术研究"(编号:D2015012)研究成果之一 公安部技术研究计划基科费项目"Hadoop架色下基于KNN文本分类算法的公安情报分析关键技术研究"(编号:2016JSYJC57)研究成果之一
关键词 LB数据 突发事件 情报体系 情报预警 数据挖掘 研判模型 LBS data emergency intelligence system inteUigence warning data mining analysis model
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  • 1兰德.论信息与情报的区别[J].科研管理,1986,7(4):17-22. 被引量:5
  • 2刘经南.泛在测绘与泛在定位的概念与发展[J].数字通信世界,2011(S1):28-30. 被引量:31
  • 3蔡亚航.关于强化情报信息主导警务战略的思考[J].公安研究,2008,0(11):72-75. 被引量:3
  • 4中华人民共和国突发事件应对法[J].中华人民共和国国务院公报,2007(30):16-23. 被引量:9
  • 5Sadilek A, Kautz H A, Silenzio V. Modeling Spread of Disease from Social InteractionsEC. The 6th International AAAI Conference on Weblogs and Social Media (ICWSM), Dublin, 2012.
  • 6Pentland A. Socially Aware, Computation and CommunicationJ. Computer, 2005, 38(3): 33-40.
  • 7Sadilek A, Kautz H, Bigham J P. Finding Your Friends and Following them to Where You Are[-CJ. The 6th ACM International Conference on Web Search and Data Mining, New York, 2012.
  • 8Sakaki T, Okazaki M, Matsuo Y. Tweet Analysis for Real-time Event Detection and Earthquake Re-porting System Development l J]. IEEE Trans. Knowl. Data Eng., 2013, 25(4): 919-931.
  • 9Song X, Zhang Q, Sekimoto Y, et al. An Intelli- gent System for Largscale Disaster Behavior Anal- ysis and Reasoning[J]. IEEE, 2013, 28(4) :35-42.
  • 10Song X, Zhang Q, Sekimoto Y, et al. Modeling and Probabilistic Reasoning of Population Evacua- tion During Large-scale Disaster[C]. The 19th ACM SIGKDD International Conference on Knowl- edge Discovery and Data Mining, New York, 2013.

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