Algorithm Research & Explore
|
2595-2599

Semi-supervised node classification based geometric neighbor

Cheng Tianying
Wang Qian
Yuan Ding
College of Computer, Chongqing University, Chongqing 400044, China

Abstract

The existent node classification methods based on network structure only pay attention to local network connection relationship. For obtaining wider network information, this paper developed a semi-supervised node classification algorithm(CBGN) based on geometric neighbor structure information. This algorithm improved random walk strategy with penalty factor in network to obtain arbitrary length node sequence for each node. It input these node sequences into the word2vec model for transforming the potential information into node vectors. CBGN combined gradient descent method and the coordinate descent method to optimize the SVM classification model. This method compared with current methods on four standard datasets. The results verify that the proposed algorithm improves the classification accuracy and has better classification effect.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.03.0110
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 9
Section: Algorithm Research & Explore
Pages: 2595-2599
Serial Number: 1001-3695(2020)09-006-2595-05

Publish History

[2020-09-05] Printed Article

Cite This Article

成天英, 王茜, 袁丁. 基于几何邻居的半监督节点分类 [J]. 计算机应用研究, 2020, 37 (9): 2595-2599. (Cheng Tianying, Wang Qian, Yuan Ding. Semi-supervised node classification based geometric neighbor [J]. Application Research of Computers, 2020, 37 (9): 2595-2599. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
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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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