In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
See More
Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 9
2631-2635,2660

Active error-correcting community discovery algorithm based on semi-supervised clustering

Zhang Xiankun
Liu Yuanbo
Ren Jing
Zhang Gaozhen
School of Computer Science & Information Engineering, Tianjin University of Science & Technology, Tianjin 300457, China
DOI: 10.19734/j.issn.1001-3695.2018.03.0162

Abstract

The classical unsupervised clustering algorithm is fast, simple and suitable for mining large-scale datasets, and it can also directly divide communities. However, due to the complexity of communities, the classification accuracy of the algorithm is not ideal. Therefore, this paper proposed an error-correcting semi-supervised community detection algorithm(ESCD) based on active learning. It can calculate the traditional K-means algorithm step by step, and adding pairs of constraints in the clustering process. In order to preserve the correct partitioning according to the prior information, it corrected the wrong division to change the connection of the network. So that the network has a more obvious block structure in the process of changing the distance between nodes and cluster centers. The results of the experiment show that compared with the existing community discovery algorithms, the ESCD algorithm has higher accuracy with less supervisory information than other semi-supervised algorithms.

Foundation Support

国家自然科学基金资助项目(61702367)
天津市教委科研计划资助项目(2017KJ033)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.03.0162
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 9
Section: Algorithm Research & Explore
Pages: 2631-2635,2660
Serial Number: 1001-3695(2019)09-015-2631-05

Publish History

[2019-09-05] Printed Article

Cite This Article

张贤坤, 刘渊博, 任静, 等. 主动纠错式半监督聚类社区发现算法 [J]. 计算机应用研究, 2019, 36 (9): 2631-2635,2660. (Zhang Xiankun, Liu Yuanbo, Ren Jing, et al. Active error-correcting community discovery algorithm based on semi-supervised clustering [J]. Application Research of Computers, 2019, 36 (9): 2631-2635,2660. )

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)