IDEAS home Printed from https://ideas.repec.org/a/ids/injdan/v16y2024i2p207-221.html
   My bibliography  Save this article

FESSARec: explaining course recommendations using fuzzy expert system and self-attention

Author

Listed:
  • Mehbooba P. Shareef
  • Babita Roslind
  • Jimson Mathew

Abstract

Recommendations generated by a model become more convincing when the system is capable of explaining the rationale behind the recommendations with respect to various decision parameters involved. A recommendation system which uses fuzzy expert system and self attention (FESSARec) to explain the recommendations is proposed here. The self-attention module extracts features of learners and courses and generates attention weights which will be used to explain the recommendations. The fuzzy expert system extracts relevant rules from the additional domain knowledge available in the datasets. As a result of this hybrid approach, FESSARec outperforms the recent architectures with which it is compared and obtains a very small root mean square error (RMSE) score of 0.65. FESSARec is also capable of producing top-N recommendations with a very high NDCG of 0.89 and HR of 0.72. It outperforms the best e-commerce baseline by 8% and the educational baseline by 16% of lower error rates.

Suggested Citation

  • Mehbooba P. Shareef & Babita Roslind & Jimson Mathew, 2024. "FESSARec: explaining course recommendations using fuzzy expert system and self-attention," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 16(2), pages 207-221.
    • Handle: RePEc:ids:injdan:v:16:y:2024:i:2:p:207-221
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=137870
    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.

    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:ids:injdan:v:16:y:2024:i:2:p:207-221. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=282 .

    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.