IDEAS home Printed from https://ideas.repec.org/a/igg/jkbo00/v12y2022i2p1-13.html
   My bibliography  Save this article

Visual Chatbot for Knowledge Transfer: What Challenges Lie Ahead?

Author

Listed:
  • Sarra Bouzayane

    (Audensiel, France)

  • Arezki Aberkane

    (Audensiel, France)

Abstract

This paper proposes an approach to design a visual chatbot to enhance the virtual knowledge sharing process. Existing chatbots are either textual or vocal whose performance has not exceeded 60%. However, in various fields a textual description is no longer sufficient, and it is so essential for users to exchange images to better express their preferences. This prevents them from individually describing the image content and transmitting it in writing, which is not always obvious. This work developed a preliminary version of a visual chatbot called SIRSBot (Smart Information Retrieval System roBot). The objective of this paper is to make experiments to identify the main challenges which may face visual information identification. The role of the visual chatbot is (1) to understand the user request, (2) to extract the characteristics of each object in the image that ultimately represent the user's preferences and finally (3) to find a response that meets the user's needs.

Suggested Citation

  • Sarra Bouzayane & Arezki Aberkane, 2022. "Visual Chatbot for Knowledge Transfer: What Challenges Lie Ahead?," International Journal of Knowledge-Based Organizations (IJKBO), IGI Global, vol. 12(2), pages 1-13, April.
    • Handle: RePEc:igg:jkbo00:v:12:y:2022:i:2:p:1-13
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJKBO.295079
    Download Restriction: no
    ---><---

    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:igg:jkbo00:v:12:y:2022:i:2:p:1-13. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.