Technology of Network & Communication
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 5
1508-1513,1519

Exploring heterogeneous variational hypergraph autoencoder for hyper-edge link prediction

Yang Weiyinga,b
Wang Yinga,b,c
Wu Yueb,c
a. College of Software, b. Key Laboratory of Symbol Computation & Knowledge Engineering, Ministry of Education, c. College of Computer Science & Technology, Jilin University, Changchun 130012, China
DOI: 10.19734/j.issn.1001-3695.2020.06.0191

Abstract

How to use hyper-edge to model the multiple association relationship in network data and realize the prediction of potential hyper-edge link relationship has important practical significance. Existing link prediction methods mainly focus on networks with pairwise relationships. However, directly applying existing link prediction methods to hyper-edge link prediction in hypergraph networks has certain limitations. Therefore, this paper proposed a hyper-edge link prediction model, called HVGAE(heterogeneous variational hypergraph autoencoder) based on heterogeneous variational hypergraph autoencoder. Firstly, this method used hypergraph convolution to realize variational hypergraph autoencoder, and converted the hypergraph network data into a low-dimension representation. Then it added nodes near-neighbor similarity function to retain the structural information to the largest degree, so as to construct heterogeneous hyper-edge link prediction model. Experiments on three diffe-rent types of hypergraph networks, the results show that HVGAE model has gained better prediction result compared with that of other baseline methods, indicating that it can better solve the problem of hyper-edge link prediction in the hypergraph network.

Foundation Support

国家自然科学基金资助项目(61872161,61602057,61976103)
吉林省科技发展计划资助项目(2018101328JC)
吉林省科技厅优秀青年人才基金资助项目(20170520059JH)
吉林省技术攻关项目(20190302029GX)
吉林省发改委项目(2019C053G-8)
吉林省教育厅科研项目(JJKH20191257KJ)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.06.0191
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 5
Section: Technology of Network & Communication
Pages: 1508-1513,1519
Serial Number: 1001-3695(2021)05-042-1508-06

Publish History

[2021-05-05] Printed Article

Cite This Article

杨伟英, 王英, 吴越. 面向异质变分超图自动编码器的超边链接预测模型 [J]. 计算机应用研究, 2021, 38 (5): 1508-1513,1519. (Yang Weiying, Wang Ying, Wu Yue. Exploring heterogeneous variational hypergraph autoencoder for hyper-edge link prediction [J]. Application Research of Computers, 2021, 38 (5): 1508-1513,1519. )

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.

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