IDEAS home Printed from https://ideas.repec.org/a/arp/tjssrr/2018p161-165.html
   My bibliography  Save this article

User Influence on Knowledge Grid Model among Big Data Community to Promote Knowledge Sharing

Author

Listed:
  • Sara Hosseinioun*

    (Universiti Putra Malaysia, Malaysia)

  • Rusli Abdullah

    (University Putra Malaysia, Malaysia)

Abstract

The significance of big data has benefited various organizations to improve their decision making, services and, productivity, while knowledge grid provides the platform to effectively capture, share, publish and manage knowledge resources to answer the questions from masses of data. However, the user’s role in these process and it influences still unclear. Therefore, this paper aimed to analyses the users impact in knowledge grid components in big data community. In this way, the research narrows the big data community members to data scientists who are able to make the structure for large quantities of formless data. This study flows the user’s roles from the human layer of knowledge grid to the other layers and combined it findings with user’s expectation of suitable model to promote knowledge sharing to clear the community member’s roles from the first step of designing a knowledge grid model till the facilitating knowledge sharing.

Suggested Citation

  • Sara Hosseinioun* & Rusli Abdullah, 2018. "User Influence on Knowledge Grid Model among Big Data Community to Promote Knowledge Sharing," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 161-165:2.
    • Handle: RePEc:arp:tjssrr:2018:p:161-165
    as

    Download full text from publisher

    File URL: https://www.arpgweb.com/pdf-files/spi2.57.161-165.pdf
    Download Restriction: no
    File URL: https://www.arpgweb.com/journal/7/special_issue/11-2018/2/4
    Download Restriction: no
    ---><---

    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:arp:tjssrr:2018:p:161-165. 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: Managing Editor (email available below). General contact details of provider: http://arpgweb.com/?ic=journal&journal=7&info=aims .

    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.