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Advanced Hybrid Information Processing. 7th EAI International Conference, ADHIP 2023, Harbin, China, September 22-24, 2023, Proceedings, Part I

Research Article

Research on Personalized Push of Mobile Education Resources Based on Mobile Social Network Big Data

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-50543-0_31,
        author={Huibing Cao},
        title={Research on Personalized Push of Mobile Education Resources Based on Mobile Social Network Big Data},
        proceedings={Advanced Hybrid Information Processing. 7th EAI International Conference, ADHIP 2023, Harbin, China, September 22-24, 2023, Proceedings, Part I},
        proceedings_a={ADHIP},
        year={2024},
        month={3},
        keywords={Mobile Social Network Big Data Educational Resources Personalized Push Resource Matching},
        doi={10.1007/978-3-031-50543-0_31}
    }
    
  • Huibing Cao
    Year: 2024
    Research on Personalized Push of Mobile Education Resources Based on Mobile Social Network Big Data
    ADHIP
    Springer
    DOI: 10.1007/978-3-031-50543-0_31
Huibing Cao1,*
  • 1: College of Digital Economics, Nanning University
*Contact email: caohuibing1979@163.com

Abstract

Nowadays, mobile social networks and mobile educational resources have become two mainstream directions in internet applications. How to combine these two to achieve more personalized and intelligent learning resource push has become a relatively important research direction. Therefore, the research on personalized push of mobile education resources based on mobile social network Big data is proposed. Starting from the mobile social network, the user interest model is constructed by using Big data analysis technology, machine learning, recommendation system and other technical means, and it is matched with the mobile education resource database to achieve personalized recommendation of education resources. The experimental results demonstrate that this method has high recommendation accuracy, with a recommendation accuracy of 95%. It can provide intelligent and efficient learning resource push solutions for mobile learning, promoting the development of mobile learning.

Keywords
Mobile Social Network Big Data Educational Resources Personalized Push Resource Matching
Published
2024-03-24
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-50543-0_31
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