Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 4
1084-1087,1096

Robust clustering algorithm based on joint structured graph learning and l1-norm spectral embedding

Tang Liwei
Zhang Jiahui
Peng Yong
Kong Wanzeng
School of Computer Science & Technology, Hangzhou Dianzi University, Hangzhou 310018, China
DOI: 10.19734/j.issn.1001-3695.2020.01.0034

Abstract

The spectral clustering may cause two limitations: a) this two-stage strategy breaks down the connection between the graph construction and the calculation of spectral eigenvectors; b) the l2-norm based similarity measure between spectral eigenvectors is usually sensitive to noise. To deal with these two limitations, this paper proposed a robust clustering algorithm based on joint structured graph learning and l1-norm spectral clustering, termed CLRL1. In the proposed framework, on one hand, the graph learning process and the clustering process could be optimized together towards the optimum; on the other hand, the l1-norm similarity measure of spectral eigenvectors was used to improve the model robustness. Experiments on extensive benchmark data sets show the effectiveness of the proposed algorithm.

Foundation Support

国家自然科学基金资助项目(61971173,61602140)
浙江省科技计划资助项目(2017C33049)
中国博士后科学基金资助项目(2017M620470)
浙江省新苗人才计划资助项目(2019R407030)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.01.0034
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 4
Section: Algorithm Research & Explore
Pages: 1084-1087,1096
Serial Number: 1001-3695(2021)04-022-1084-04

Publish History

[2021-04-05] Printed Article

Cite This Article

汤立伟, 张家珲, 彭勇, 等. 联合结构化图学习与l1范数谱嵌入的鲁棒聚类算法 [J]. 计算机应用研究, 2021, 38 (4): 1084-1087,1096. (Tang Liwei, Zhang Jiahui, Peng Yong, et al. Robust clustering algorithm based on joint structured graph learning and l1-norm spectral embedding [J]. Application Research of Computers, 2021, 38 (4): 1084-1087,1096. )

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)