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Algorithm Research & Explore
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1393-1397,1408

Based on nonnegative matrix factorization for link prediction model via multiple information combination modes

Tang Minghu
School of Computer, Qinghai Nationnalities University, Xining 810007, China

Abstract

Aiming at network sparsity and noise problem in link prediction algorithm based on topological structure similarity, this paper proposed a link prediction model based on non-negative matrix decomposition. The model started from the micro and macro levels, and simultaneously integrated the internal and external auxiliary information of the network, which mitigated the impact of network sparsity and improved the overall performance of the algorithm prediction. The proposed three information combination models reflected the information fusion strategy from macro and micro perspectives. The experimental results on 13 real network datasets demonstrate the superiority of algorithm prediction performance.

Foundation Support

青海省应用基础研究项目(2018-ZJ-707)
国家教育部“春晖计划”合作科研项目(2019)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.04.0100
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 5
Section: Algorithm Research & Explore
Pages: 1393-1397,1408
Serial Number: 1001-3695(2021)05-020-1393-05

Publish History

[2021-05-05] Printed Article

Cite This Article

唐明虎. 基于多种信息组合模式的非负矩阵分解链路预测模型 [J]. 计算机应用研究, 2021, 38 (5): 1393-1397,1408. (Tang Minghu. Based on nonnegative matrix factorization for link prediction model via multiple information combination modes [J]. Application Research of Computers, 2021, 38 (5): 1393-1397,1408. )

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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