摘要
针对当前用于提取突发事件的方法存在精度低和效率低的问题,提出一种基于词相关性特征的突发事件检测方法,能从社会网络数据流中快速地检测出突发事件,以便相关的决策者可以及时有效地采取措施进行处理,使突发事件的负面影响被尽量降低,维护社会的安定。仿真结果表明,突发事件检测方法在实时博文数据流中具有很好的事件检测效果,与已有的方法相比,所提方法可以满足突发事件检测的需求,不仅能检测到子事件的详细信息,而且能准确地检测出事件的相关信息。
For current methods for extracting emergencies had problems of low accuracy and low efficiency,an emergency detection method based on the characteristics of word correlation was proposed,which could quickly detect emergency events from the social network data stream,so that relevant decision makers could take timely and effective measures to deal with,making the negative impact of emergencies can be reduced as much as possible to maintain social stability.The simulation results show that the emergency event detection method has a better event detection effect in the real-time blog post data stream.Compared with the existing methods,the proposed method can meet the needs of emergency detection.Not only the detailed information of the sub-events can be detected,but also the related information of the events can be accurately detected.
作者
蒋伟进
王扬
刘晓亮
吕斯健
JIANG Weijin;WANG Yang;LIU Xiaoliang;LYU Sijian(Institute of Big Data and Internet Innovation,Hunan University of Technology and Business,Changsha 410205,China;Key Laboratory of Hunan Province for New Retail Virtual Reality Technology,Changsha 410205,China;College of Computer and Information Engineering,Hunan University of Technology and Business,Changsha 410205,China;School of Computer Science and Technology,Wuhan University of Technology,Wuhan 430073,China)
出处
《通信学报》
EI
CSCD
北大核心
2020年第12期193-204,共12页
Journal on Communications
基金
国家自然科学基金资助项目(No.61472136,No.61772196)
湖南省自然科学基金资助项目(No.2020JJ4249)
湖南省社会科学基金重点资助项目(No.2016ZDB006)
湖南省社会科学成果评审委员会课题重点基金资助项目(湘社评19ZD1005)
湖南省学位与研究生教育改革研究基金资助项目(No.2020JGYB234)
湖南省研究生科研创新资助项目(No.CX20201074)。
关键词
突发事件
单词关系图
多归属谱聚类
检测
emergency
word relationship graph
multi-attribute spectral clustering
detection
