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App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 11

Large-scale graph layout algorithm based on multi-level stochastic gradient descent

Zhou Yingxin1a
Li Xuejun1a
Wu Yadong2
Zhang Hongying1b
Wang Jiao1b
Zhang Qiumei1a
Wang Guijuan1a,1b
1. a. School of Computer Science & Technology, b. School of Information Engineering, Southwest University of Science & Technology, Mianyang Sichuan 621000, China
2. School of Computer Science & Engineering, Sichuan University of Science & Engineering, Zigong Sichuan 643000, China
DOI: 10.19734/j.issn.1001-3695.2024.03.0073

Abstract

Large-scale graph layout remains a prominent focus in graph visualization research. While the stress model excels in representing global structure, its speed lags behind the spring-electric model, and its local structure quality is suboptimal. This paper proposed a graph layout algorithm, aimed at enhancing the efficiency of layout while preserving global structure and improving local quality. The model first utilized graph compression based on neighbor structure to generate a hierarchical graph structure, and then the node optimal placement algorithm was used to initialize the node coordinates. Next, it improved the local quality of layout using a SGD layout algorithm based on positive and negative samples, and further enhanced the layout speed through multi-level algorithm. Finally, comparative experiments with existing layout models on 30 datasets of different scales demonstrate the effectiveness of the proposed model in terms of efficiency, layout quality and visualization.

Foundation Support

四川省自然科学基金项目(24NSFSC5113)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.03.0073
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 11

Publish History

[2024-05-20] Accepted Paper

Cite This Article

周颖鑫, 李学俊, 吴亚东, 等. 基于多层次随机梯度下降的大规模图布局算法 [J]. 计算机应用研究, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.03.0073. (Zhou Yingxin, Li Xuejun, Wu Yadong, et al. Large-scale graph layout algorithm based on multi-level stochastic gradient descent [J]. Application Research of Computers, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.03.0073. )

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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