IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i10p1649-d1658325.html
   My bibliography  Save this article

A Bidirectional Material Diffusion Algorithm Based on Fusion Hypergraph Random Walks for Video Recommendation

Author

Listed:
  • Yibo Sun

    (Faculty of Sciences, Engineering and Technology, The University of Adelaide, Adelaide, SA 5000, Australia)

  • Lei Yue

    (Post Big Data Technology and Application Engineering Research Center of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
    Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology), Nanjing University of Posts and Telecommunications, Nanjing 210003, China)

  • Tao He

    (Post Big Data Technology and Application Engineering Research Center of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
    Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology), Nanjing University of Posts and Telecommunications, Nanjing 210003, China)

  • Weitong Chen

    (Faculty of Sciences, Engineering and Technology, The University of Adelaide, Adelaide, SA 5000, Australia)

  • Zhe Sun

    (Post Big Data Technology and Application Engineering Research Center of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
    Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology), Nanjing University of Posts and Telecommunications, Nanjing 210003, China)

Abstract

With the rapid popularization of video software, video recommendation algorithms have become crucial for ensuring the quality of video platforms. This study focuses on video tags and constructs a ternary structure of user–video–tags. It proposes a bidirectional material diffusion algorithm based on fusion hypergraph random walks for video recommendation. The effectiveness of the proposed algorithm is validated by comparing it with existing algorithms on public datasets.

Suggested Citation

  • Yibo Sun & Lei Yue & Tao He & Weitong Chen & Zhe Sun, 2025. "A Bidirectional Material Diffusion Algorithm Based on Fusion Hypergraph Random Walks for Video Recommendation," Mathematics, MDPI, vol. 13(10), pages 1-21, May.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:10:p:1649-:d:1658325
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/10/1649/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/13/10/1649/
    Download Restriction: no
    ---><---

    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:gam:jmathe:v:13:y:2025:i:10:p:1649-:d:1658325. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.