IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-724-3_29.html

Design of Resource Recommendation System for Social Work Service Object Based on Collaborative Filtering

In: Proceedings of the 2025 5th International Conference on Informatization Economic Development and Management (IEDM 2025)

Author

Listed:
  • Haonan Zeng

    (University of Leeds, School of Politics and International Studies & Sociology and Social Policy)

Abstract

With the continuous development of social work, improving the matching degree between service objects and resources, and enhancing service efficiency and quality, has become an urgent problem to be solved. This paper designs a resource recommendation system for social work service objects based on collaborative filtering. The system adopts a B/S (Browser/Server) architecture and is developed using the SSH framework and MVC (Model-View-Controller) technology, ensuring the security, simplicity, and scalability of the system. In terms of functionality, the resource recommendation system includes key modules such as user management, resource management, recommendation algorithm implementation, and a feedback mechanism, providing comprehensive related services. Utilizing project-based collaborative filtering technology, the system recommends the most relevant resources to service objects by calculating the similarity between resources. This system can offer more accurate and personalized resource recommendations for social work service objects, thereby improving the overall effectiveness of social work services and promoting the healthy development of the social work industry.

Suggested Citation

  • Haonan Zeng, 2025. "Design of Resource Recommendation System for Social Work Service Object Based on Collaborative Filtering," Advances in Economics, Business and Management Research, in: Meilin Zhang & Au Yong Hui Nee & Khurram Shehzad & Sameer Kumar & Ehsan Javanmardi (ed.), Proceedings of the 2025 5th International Conference on Informatization Economic Development and Management (IEDM 2025), pages 297-303, Springer.
  • Handle: RePEc:spr:advbcp:978-94-6463-724-3_29
    DOI: 10.2991/978-94-6463-724-3_29
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:spr:advbcp:978-94-6463-724-3_29. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.