App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 10

Incremental multi-view clustering via sparse graph learning

Pan Xiaoyan1
Chen Deyou1
Yan Xiaoqiang2
1. School of Information Engineering, Zhengzhou College of Finance and Economics, Zhengzhou 450000, China
2. School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou 475400, China
DOI: 10.19734/j.issn.1001-3695.2026.03.0036

Abstract

Conventional multi-view clustering methods usually assume that all views are available at once, limiting the scope of application only on real world problems where views come in a sequential manner over time. In order to overcome this, this paper presents Sparse Graph-based Incremental Multi-view Clustering (SG-IMVC) . Firstly, this paper designs a late-fusion rotation matrix learning approach to learn the optimal linear transformation between historical and newly arrived views. Second, this paper proposes an inverse distance adaptive weighting strategy based on sparse graph reconstruction error, which automatically balances the influence of historical views and new views on clustering. Finally, this paper presents a consistent partition enhancement mechanism integrating sparse graph learning and eigenvalue decomposition, in which the consistent sparse graph performs the Eigenvalue decomposition to derive a more optimal clustering partition matrix. Experimental results on six multi-view datasets including IXMAS, WVU, Handwritten, DMD, YouTube and ESP demonstrate that SG-IMVC achieves average improvements of 2.28%, 6.88% and 6.47% in ACC, NMI and ARI metrics respectively compared with the second-best baseline algorithm, verifying its superiority in incremental scenarios.

Foundation Support

河南省自然科学基金面上项目(252300421504)
河南省科技攻关项目(262102210263)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.03.0036
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 10

Publish History

[2026-06-30] Accepted Paper

Cite This Article

潘笑颜, 陈得友, 闫小强. 基于稀疏图学习的增量多视图聚类算法 [J]. 计算机应用研究, 2026, 43 (10). (2026-07-30). https://doi.org/10.19734/j.issn.1001-3695.2026.03.0036. (Pan Xiaoyan, Chen Deyou, Yan Xiaoqiang. Incremental multi-view clustering via sparse graph learning [J]. Application Research of Computers, 2026, 43 (10). (2026-07-30). https://doi.org/10.19734/j.issn.1001-3695.2026.03.0036. )

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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