YanShan University, Qinhuangdao 066004, China.
J Environ Public Health. 2022 Sep 25;2022:3183195. doi: 10.1155/2022/3183195. eCollection 2022.
Big data improves opportunities for enhancing and improving university students' IPE. In order to improve the accessibility of IPE for university students, this study integrates big-data techniques into the IPE (Ideological and Political Education) model of university students and builds the IPE platform. This study presents the idea of user rating sparsity and employs a two-step training strategy to address the issues of user cold start and sparse data in light of the drawbacks of conventional methods. This algorithm produces a very small data structure, which saves a lot of storage space. This study also uses hybrid recommendation technology, which effectively enables platform users to select customized update resources based on their interest information. According to test results, this method's suggestion accuracy can reach 95.69%, and it has a high user rating. This demonstrates that the method is reliable and accomplishes the desired result. This paper fully utilizes mega data to improve the accessibility of IPE for university students.
大数据为增强和改善大学生IPE 提供了更多机会。为了提高大学生 IPE 的可及性，本研究将大数据技术融入到大学生的 IPE（思想政治教育）模型中，并构建了 IPE 平台。本研究提出了用户评分稀疏的概念，并采用两步训练策略来解决传统方法的用户冷启动和数据稀疏问题。该算法生成的数据结构非常小，节省了大量存储空间。本研究还使用了混合推荐技术，能够根据平台用户的兴趣信息，为他们有效地选择定制化的更新资源。根据测试结果，该方法的建议准确率可以达到 95.69%，且用户评分较高。这表明该方法是可靠的，能够达到预期的效果。本文充分利用大数据来提高大学生 IPE 的可及性。
