IDEAS home Printed from https://ideas.repec.org/a/vrs/brcebe/v1y2015i1p8n24.html
   My bibliography  Save this article

Teaching Natural Language Processing (NLP) Using Ontology Based Education Design

Author

Listed:
  • Rehman Zobia

    (COMSATS Institute of Information Technology, Abbottabad, Pakistan Lucian Blaga University of Sibiu, Romania)

  • Kifor Stefania

    (Lucian Blaga University of Sibiu, Romania)

Abstract

It often happens in teaching that due to complexity of a subject or unavailability of an expert instructor the subject undergoes in a situation that not only affects its outcome but the involvement and learning development of students also. Although contents are covered even in such a situation but their inadequate explanation leaves many question marks in students’ mind. Artificial Intelligence helps represent knowledge graphically and symbolically which can be logically inferred. Visual and symbolic representation of knowledge is easy to understand for both teachers and students. To facilitate students understanding teachers often structure domain knowledge in a visual form where all important contents of a subject can be seen along with their relation to each other. These structures are called ontology which is an important aspect of knowledge engineering. Teaching via ontology is in practice since last two decades. Natural Language Processing (NLP) is a combination of computation and linguistic and is often hard to teach. Its contents are apparently not tied together in a reasonable way which makes it difficult for a teacher that where to start with. In this article we will discuss the design of ontology to support rational learning and efficient teaching of NLP at introductory level.

Suggested Citation

  • Rehman Zobia & Kifor Stefania, 2015. "Teaching Natural Language Processing (NLP) Using Ontology Based Education Design," Balkan Region Conference on Engineering and Business Education, Sciendo, vol. 1(1), pages 1-8, November.
  • Handle: RePEc:vrs:brcebe:v:1:y:2015:i:1:p:8:n:24
    DOI: 10.1515/cplbu-2015-0024
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/cplbu-2015-0024
    Download Restriction: no

    File URL: https://libkey.io/10.1515/cplbu-2015-0024?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
    ---><---

    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:vrs:brcebe:v:1:y:2015:i:1:p:8:n: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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.