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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 4
992-996,1005

Research on evolutionary community discovery algorithm in dynamic weighted networks

Zhang Gaozhen
Zhang Xiankun
Su Jing
Liu Yuanbo
School of Computer Science & Information Engineering, Tianjin University of Science & Technology, Tianjin 300457, China
DOI: 10.19734/j.issn.1001-3695.2017.10.0966

Abstract

In dynamic networks, detecting community structure is a very complex and meaningful process, which can better observe and analyze the evolution of the networks. For the community detection problem in dynamic weighted networks, this paper proposed an algorithm combining the community structure of the historical networks, called the evolutionary community discovery algorithm(ECDA) in dynamic weighted networks. The algorithm was divided into two steps: a) calculated the input matrix of the current timestep by combining the information of historical communities and network structure; b) and then calculated the result of community detection combining the historical timestep information through the input matrix. The algorithm has the following advantages: a) it can automatically discover the community structure of each timestep in the dynamic weighted network; b) the algorithm has a high sensitivity to the changes of network structure and the changes of community structure. And the experimental results show that the proposed algorithm can effectively detect the community structure in dynamic weighted networks, and it is quite competitive with other algorithms.

Foundation Support

国家自然科学基金资助项目(61702367)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.10.0966
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 4
Section: Algorithm Research & Explore
Pages: 992-996,1005
Serial Number: 1001-3695(2019)04-008-0992-05

Publish History

[2019-04-05] Printed Article

Cite This Article

张高祯, 张贤坤, 苏静, 等. 动态加权网络中的演化社区发现算法研究 [J]. 计算机应用研究, 2019, 36 (4): 992-996,1005. (Zhang Gaozhen, Zhang Xiankun, Su Jing, et al. Research on evolutionary community discovery algorithm in dynamic weighted networks [J]. Application Research of Computers, 2019, 36 (4): 992-996,1005. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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