IDEAS home Printed from https://ideas.repec.org/a/hin/complx/8919625.html
   My bibliography  Save this article

Optimization of Human Resource File Information Decision Support System Based on Cloud Computing

Author

Listed:
  • Chunling Cai
  • Chuanyi Chen
  • Zhihan Lv

Abstract

With the rapid development of science and technology era, human resources and knowledge resources have become an important part of the development of enterprises. Therefore, it is very necessary to establish human resources data pool and carry out data mining based on it, so as to extract high quality and high quantity information to provide support for managers’ decision-making. In this study, the human resource archive information decision support system (DSS) is developed for various management and decision-making works by taking advantage of the characteristics of cloud computing, such as large scale, high reliability, versatility, and high expansibility. Based on the analysis of “cloud computing†advantages in resources integration and sharing and so on, on the basis of this system is designed by using the basis of the data acquisition layer, support layer of network services, cloud computing support layer, data standardization conversion layer, system application layer, system layer, decision support layer and so on 7 layer architecture, discusses the features and functions of each layer structure, the working mode and working mode of the Decision Support System (DSS) are introduced in detail. The system makes up for the defects of the traditional archive management, such as the lack of data resources, the inability to realize the isomorphism, and standardized processing of the data from multiple data sources.

Suggested Citation

  • Chunling Cai & Chuanyi Chen & Zhihan Lv, 2021. "Optimization of Human Resource File Information Decision Support System Based on Cloud Computing," Complexity, Hindawi, vol. 2021, pages 1-12, June.
  • Handle: RePEc:hin:complx:8919625
    DOI: 10.1155/2021/8919625
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/complexity/2021/8919625.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/complexity/2021/8919625.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2021/8919625?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:complx:8919625. 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.