IDEAS home Printed from https://ideas.repec.org/a/alk/jcsts0/v7y2025i7id10001.html

Improving the performance of recommender systems based on blockchain technology

Author

Listed:
  • Milad Javadi

    (Ph.D student, College of Business, Finance, Florida Atlantic University, USA)

  • Maryam Mazrooie

    (PhD Student, Department of Economics, Maxwell School of Citizenship & Public Affairs, Syracuse University, USA)

  • Azin Bohlool

    (Islamic Azad University, Tehran Science and Research University Branch (Saveh), IRAN)

Abstract

Blockchain technology has received the focus of many scientists as a promising technology in distributed systems. It was made possible by blockchain aspects such as visibility and Permanence. The newness of blockchain technology causes many challenges in this field. One of these challenges is managing data in the blockchain and presenting data suitable to the user's interests. In current centralized systems, recommender systems have solved this challenge. Implementing recommender systems in blockchain intelligent contracts and raising the transaction cost make the recommendations inaccurate due to the lack of complex calculation facilities of machine learning algorithms in innovative contract programming languages. They were introducing a novel method for enhancing recommender systems using blockchain technology. This method involves storing data in the blockchain according to a structure stipulated within the smart contract. The data is then provided to the off-chain recommender system through the public key of the smart contract, enabling the necessary processing for providing the appropriate recommendation to the user. The results are then stored in the blockchain and presented to the user during a transaction. The results of this method, as compared to previous research and works, demonstrate that performing complex calculations outside the chain not only reduces the transaction cost of establishing a contract but also decreases the transaction cost related to the recommender in the proposal system in terms of gas consumption, leading to increased scalability.

Suggested Citation

  • Milad Javadi & Maryam Mazrooie & Azin Bohlool, 2025. "Improving the performance of recommender systems based on blockchain technology," Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 7(7), pages 431-448, June.
  • Handle: RePEc:alk:jcsts0:v:7:y:2025:i:7:id:10001
    DOI: 10.32996/jcsts.2025.7.7.48
    as

    Download full text from publisher

    File URL: https://al-kindipublisher.com/index.php/jcsts/article/view/10001
    File Function: Abstract page
    Download Restriction: no

    File URL: https://al-kindipublisher.com/index.php/jcsts/article/download/10001/9212
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.32996/jcsts.2025.7.7.48?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

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:alk:jcsts0:v:7:y:2025:i:7:id:10001. 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: Al-Kindi Center for Research and Development (email available below). General contact details of provider: https://al-kindipublisher.com/index.php/jcsts .

    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.