In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
See More
Technology of Network & Communication
|
App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 7
2124-2131

Link prediction combing nonnegative matrix factorization and directed structure

Chen Guangfu1,2
Guo Lei1,2
Lian Yanping1
1. College of Mathematics & Computer Science, Wuyi University, Wuyishan Fujian 354399, China
2. Fujian Key Laboratory of Big Data Application & Intellectualization for Tea Industry, Wuyishan Fujian 354399, China
DOI: 10.19734/j.issn.1001-3695.2021.12.0656

Abstract

The existing link prediction methods for directed networks only consider single-type network structures but ignore some key network structures, which leads to the decrease of prediction accuracy. To solve this problem, this paper proposed a link prediction framework which combined multi-type directed network structure and non-negative matrix factorization to preserve local and global structure information. Firstly, it mapped the adjacency matrix of directed network to the low-dimensional latent space to preserve the directional link of the original network. Secondly, it fused four key directed structural similarities including DCN, DAA, DRA and potential theory(BF) by 2-norm and normalised Laplacian to maintain information on the structure of multi-type networks. Then, it proposed four link prediction models NMF-DNS-DCN, NMF-DNS-DAA, NMF-DNS-DRA and NMF-DNS-BF respectively. Finally, this paper enabled multiplicative update rules to learn the parameters of the four models and proved the convergence of the proposed algorithms. Compared with the existing representative methods on 8 real-world directed networks, the AUC, recall and F1 of the proposed model is increased by 5.3%, 7.8% and 6%, respectively.

Foundation Support

福建省自然科学基金资助项目(2021J011146,2021J011144)
武夷学院引进人才科研启动基金资助项目(YJ202017)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.12.0656
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 7
Section: Technology of Network & Communication
Pages: 2124-2131
Serial Number: 1001-3695(2022)07-033-2124-08

Publish History

[2022-02-18] Accepted Paper
[2022-07-05] Printed Article

Cite This Article

陈广福, 郭磊, 连雁平. 融合有向结构和非负矩阵分解的链路预测 [J]. 计算机应用研究, 2022, 39 (7): 2124-2131. (Chen Guangfu, Guo Lei, Lian Yanping. Link prediction combing nonnegative matrix factorization and directed structure [J]. Application Research of Computers, 2022, 39 (7): 2124-2131. )

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.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)