IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v15y2024i2d10.1007_s13198-022-01783-2.html
   My bibliography  Save this article

Extractive text summarization of arabic multi-document using fuzzy C-means and Latent Dirichlet Allocation

Author

Listed:
  • Ahmad T. Al-Taani

    (Yarmouk University)

  • Sami H. Al-Sayadi

    (Yarmouk University)

Abstract

In this research, we investigated the performance of the combination of fuzzy c-means and latent Dirichlet allocation algorithms for Arabic multi-document summarization. The summary should include the most essential sentences from multi-documents with the same topic. The TAC-2011 corpus is used for experiments, first, the documents in the corpus are clustered using fuzzy c-means algorithm. The aim of the clustering process here is to classify the documents according to their topics, e.g., economic, politic, sport, etc. The results are compared against some recent Arabic summarization approaches that used ant colony and discriminant analysis algorithms. The proposed approach has obtained competitive results compared to those recent approaches.

Suggested Citation

  • Ahmad T. Al-Taani & Sami H. Al-Sayadi, 2024. "Extractive text summarization of arabic multi-document using fuzzy C-means and Latent Dirichlet Allocation," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(2), pages 713-726, February.
    • Handle: RePEc:spr:ijsaem:v:15:y:2024:i:2:d:10.1007_s13198-022-01783-2
    DOI: 10.1007/s13198-022-01783-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-022-01783-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-022-01783-2?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:spr:ijsaem:v:15:y:2024:i:2:d:10.1007_s13198-022-01783-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.