Multi-attribute spectral clustering emergency detection based on word correlation feature

Weijin JIANG; Yang WANG; Xiaoliang LIU; Sijian LYU

doi:10.11959/j.issn.1000-436X.2020215

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Multi-attribute spectral clustering emergency detection based on word correlation feature

Correspondences | 更新时间：2024-06-05

- Multi-attribute spectral clustering emergency detection based on word correlation feature
- Journal on Communications Vol. 41, Issue 12, Pages: 193-204(2020)
- 作者机构：
  
  1. 湖南工商大学大数据与互联网创新研究院，湖南长沙 410205
  2. 新零售虚拟现实技术湖南省重点实验室，湖南长沙 410205
  3. 湖南工商大学计算机与信息工程学院，湖南长沙 410205
  4. 武汉理工大学计算机科学与技术学院，湖北武汉 430073
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61472136);The National Natural Science Foundation of China(61772196);The Key Project of the Natural Science Foundation of Hunan Province(2020JJ4249);The Key Social Science Fund of Hunan Provincial(2016ZDB006);The Key Social Science Achievement Review Committee of Hunan Provincial(19ZD1005);The Degree and Graduate Education Reform Research Project of Hunan Provincial(2020JGYB234);Postgraduate Scientific Research Innovation Project of Hunan Province(CX20201074)
- DOI：10.11959/j.issn.1000-436X.2020215
  CLC： TP393
- Online First：2020-12，
  
  Published：25 December 2020
- 稿件说明：
移动端阅览
Weijin JIANG, Yang WANG, Xiaoliang LIU, et al. Multi-attribute spectral clustering emergency detection based on word correlation feature[J]. Journal on Communications, 2020, 41(12): 193-204.
DOI：

Weijin JIANG, Yang WANG, Xiaoliang LIU, et al. Multi-attribute spectral clustering emergency detection based on word correlation feature[J]. Journal on Communications, 2020, 41(12): 193-204. DOI： 10.11959/j.issn.1000-436X.2020215.

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。

Abstract

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.

关键词

Keywords

references

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