Technology of Network & Communication
|
App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 10
3143-3147

Dynamic link prediction algorithm based on graph convolutional networks via temporal motif-based attention

Wu Zheng
Chen Hongchang
Zhang Jianpeng
Institute of Information Technology, PLA Strategic Support Force Information Engineering University, Zhengzhou 450003, China
DOI: 10.19734/j.issn.1001-3695.2021.01.0029

Abstract

Aiming to predict edges in the future based on historical linkage status, dynamic link prediction in temporal networks is an important component of the network analysis and has great value in theoretical research and wide applications. Concerning the problem that current dynamic link prediction algorithms mostly only consider first-order relations to infer future links, while ignoring exploiting the higher-order topological and temporal relationships among nodes, this paper proposed a dynamic link prediction algorithm based on graph convolutional network via temporal motif-based attention. Firstly, it designed a temporal motif-based adjacency matrix construction algorithm, exploiting the higher-order topological and temporal relationships among nodes. Then it modeled the evolution of temporal network with latent mediation process, while iteratively updated the low-dimensional node representations with temporal motif-based adjacency matrix as the transmission matrix in graph convolutional network. Finally, it predicted the future links based on the conditional intensity function with node representations as input. Experimental results on various real-world temporal network datasets show that the proposed algorithm can effectively mine the high-order topological and temporal information among nodes, and improve the performance of the dynamic link prediction.

Foundation Support

国家自然基金青年基金项目
郑州市协同创新重大专项
中国博士后科学基金面上项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.01.0029
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 10
Section: Technology of Network & Communication
Pages: 3143-3147
Serial Number: 1001-3695(2021)10-046-3143-05

Publish History

[2021-10-05] Printed Article

Cite This Article

吴铮, 陈鸿昶, 张建朋. 基于时序模体注意力图卷积的动态网络链路预测算法 [J]. 计算机应用研究, 2021, 38 (10): 3143-3147. (Wu Zheng, Chen Hongchang, Zhang Jianpeng. Dynamic link prediction algorithm based on graph convolutional networks via temporal motif-based attention [J]. Application Research of Computers, 2021, 38 (10): 3143-3147. )

About the Journal

  • Application Research of Computers Monthly Journal
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    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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