App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 10

Deep active semi-supervised clustering model

Fu Yanyan1,2,3
Huang Ruizhang1,2,3
Xue Jingjing1,2,3
Ren Lina1,2,3
Chen Yanping1,2,3
Lin Chuan1,2,3
1. Guizhou University, Text Computing & Cognitive Intelligence Engineering Research Center of National Education Ministry, Guiyang Guizhou 550025, China
2. Guizhou University, State Key Laboratory of Public Big Data, Guiyang Guizhou 550025, China
3. Guizhou University, College of Computer Science & Technology, Guiyang Guizhou 550025, China
DOI: 10.19734/j.issn.1001-3695.2024.01.0025

Abstract

Deep semi-supervised clustering aims to achieve better clustering results using a small amount of supervised information. However, the amount of supervised information is often limited due to the expensive labelling cost. Therefore, with limited supervisory information, it becomes crucial to select the most valuable supervisory information for clustering. To address the above problem, a Deep Active Semi-Supervised Clustering Model(DASCM) based on active learning is proposed, which designs an active learning method that is able to select marginal texts containing rich information and further generates high-value supervisory information containing edge texts. The model uses this supervised information to guide the clustering, thus improving the clustering performance. The experimental results on five real text datasets show that the clustering performance of DASCM is significantly improved. This result verifies that supervised information generated using active learning methods that cover marginal text is effective in improving clustering.

Foundation Support

国家自然科学基金资助项目(62066007)
贵州省科技支撑计划项目(黔科合支撑【2022】一般277)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.01.0025
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 10

Publish History

[2024-04-23] Accepted Paper

Cite This Article

付艳艳, 黄瑞章, 薛菁菁, 等. 基于主动学习的深度半监督聚类模型 [J]. 计算机应用研究, 2024, 41 (10). (2024-07-12). https://doi.org/10.19734/j.issn.1001-3695.2024.01.0025. (Fu Yanyan, Huang Ruizhang, Xue Jingjing, et al. Deep active semi-supervised clustering model [J]. Application Research of Computers, 2024, 41 (10). (2024-07-12). https://doi.org/10.19734/j.issn.1001-3695.2024.01.0025. )

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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