IDEAS home Printed from https://ideas.repec.org/a/igg/jdsst0/v8y2016i1p1-24.html
   My bibliography  Save this article

Towards a Novel Approach for Enterprise Knowledge Capitalization Utilizing an Ontology and Collaborative Decision-Making: Application to Inotis Enterprise

Author

Listed:
  • Fatima Zohra Benkaddour

    (Laboratoire d'Informatique Oran (LIO), Département d'Informatique, University of Oran1 Ahmed BenBella, Oran, Algeria)

  • Noria Taghezout

    (Laboratoire d'Informatique Oran (LIO), Département d'Informatique, University of Oran1 Ahmed BenBella, Oran, Algeria)

  • Bouabdellah Ascar

    (Inotis Enterprise, Oran, Algeria)

Abstract

In this paper, the authors describe the development of a Decision Support System (DSS) in the spunlace nonwoven production industry. The suggested DSS utilizes domain ontology and a collaborative platform that allows operators to share and exchange experiences in the industrial diagnosis in order to have new ideas and useful information for collaborative decision-making. One of the main aspects addressed in the decision-making process was the knowledge management of the most frequently breakdowns of machines as the card, aquajet etc. This paper introduces the architecture of the system, including several modules such as, Reasoning engine and Similarity module, etc. The decision-making is reinforced by a case-based reasoning to recommend solutions where previously solved cases (problem) are compared to recently encountered ones using the same ontology to define similarity between cases. Some experiments have been conducted in INOTIS enterprise to indicate the efficiency of the proposed system.

Suggested Citation

  • Fatima Zohra Benkaddour & Noria Taghezout & Bouabdellah Ascar, 2016. "Towards a Novel Approach for Enterprise Knowledge Capitalization Utilizing an Ontology and Collaborative Decision-Making: Application to Inotis Enterprise," International Journal of Decision Support System Technology (IJDSST), IGI Global, vol. 8(1), pages 1-24, January.
  • Handle: RePEc:igg:jdsst0:v:8:y:2016:i:1:p:1-24
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJDSST.2016010101
    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:jdsst0:v:8:y:2016:i:1:p:1-24. 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.