IDEAS home Printed from https://ideas.repec.org/a/hin/jjmath/7890658.html
   My bibliography  Save this article

Multiple Collaborative Supervision Pattern Recognition Method within Social Organizations Based on Data Clustering Algorithm

Author

Listed:
  • Wei Zhang
  • Lili Pang
  • Naeem Jan

Abstract

This paper proposes a multiple collaborative supervision pattern recognition method within social organizations based on data clustering algorithm to realize diversified supervision within social organizations and improve the effect of the said pattern recognition. Firstly, the characteristics and functions of social organizations are analyzed, and the definition of social organizations is given. Further, this paper studies the meaning and characteristics of social organization supervision, analyzes the failure of internal supervision of social organizations, and then determines the internal governance elements of social organizations. In addition, the basic steps of pattern recognition are given. Finally, multiple collaborative supervision patterns recognition within social organizations is realized based on data clustering algorithm. Experiments show that this method can improve the recognition accuracy of multiple collaborative supervision patterns and reduce the recognition time.

Suggested Citation

  • Wei Zhang & Lili Pang & Naeem Jan, 2021. "Multiple Collaborative Supervision Pattern Recognition Method within Social Organizations Based on Data Clustering Algorithm," Journal of Mathematics, Hindawi, vol. 2021, pages 1-12, December.
    • Handle: RePEc:hin:jjmath:7890658
    DOI: 10.1155/2021/7890658
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/jmath/2021/7890658.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/jmath/2021/7890658.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2021/7890658?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jjmath:7890658. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.