IDEAS home Printed from https://ideas.repec.org/a/bla/jinfst/v67y2016i11p2667-2683.html
   My bibliography  Save this article

Automated arabic text classification with P-Stemmer, machine learning, and a tailored news article taxonomy

Author

Listed:
  • Tarek Kanan
  • Edward A. Fox

Abstract

No abstract is available for this item.

Suggested Citation

  • Tarek Kanan & Edward A. Fox, 2016. "Automated arabic text classification with P-Stemmer, machine learning, and a tailored news article taxonomy," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(11), pages 2667-2683, November.
    • Handle: RePEc:bla:jinfst:v:67:y:2016:i:11:p:2667-2683
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1002/asi.23609
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sachin Kumar & Aditya Sharma & B Kartheek Reddy & Shreyas Sachan & Vaibhav Jain & Jagvinder Singh, 2022. "An intelligent model based on integrated inverse document frequency and multinomial Naive Bayes for current affairs news categorisation," 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. 13(3), pages 1341-1355, June.
    2. Sachin Kumar & Shivam Panwar & Jagvinder Singh & Anuj Kumar Sharma & Zairu Nisha, 2022. "iCACD: an intelligent deep learning model to categorise current affairs news article for efficient journalistic process," 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. 13(5), pages 2572-2582, October.

    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:bla:jinfst:v:67:y:2016:i:11:p:2667-2683. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.asis.org .

    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.