@article{4446,
  author = {Xuefeng Hu, Haijuan Zhou, Yanhua Su},
  title = {Improving the Personalized Analysis of Network Education based on Recommendation Algorithms},
  journal = {Journal of Intelligent Computing},
  year = {2025},
  volume = {16},
  number = {2},
  doi = {https://doi.org/10.6025/jic/2025/16/2/60-70},
  url = {https://www.dline.info/jic/fulltext/v16n2/jicv16n2_2.pdf},
  abstract = {With the rapid development of science and technology, the internet and new media have entered the era of
algorithmic recommendation. This article investigates and analyzes the new characteristics of content
dissemination and discourse expression in university network education from the perspective of
recommendation algorithms. Addressing the practical dilemmas of value bias at different stages of integration,
decreased independent thinking ability of learners, and divergence of social values, this study explores the
incorporation of algorithmic recommendation techniques into university network education. It proposes
guiding strategies, such as the “guiding algorithm,” “approaching algorithm,” and “moving away from
algorithm,” to provide references for the realization of “recommendation algorithm + university network
education” and promote the healthy development of university network education.},
}