Text Analysis of Student Message Based on CCSS Ten-year Follow-up Survey

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Artificial Intelligence | 更新时间：2025-09-30

- Text Analysis of Student Message Based on CCSS Ten-year Follow-up Survey
- “In the field of improving the quality of higher education, experts have proposed an improved Mini Batch K-Means clustering algorithm, which transforms short texts into long texts through clustering methods, providing input for LDA models and effectively improving the model's PMI value.”
- Software Guide Vol. 24, Issue 9, Pages: 34-40(2025)
- 作者机构：
  
  1.南京邮电大学电子与光学工程学院、柔性电子（未来技术）学院
  2.南京邮电大学教学质量监控与评估中心，江苏南京 210023
- 作者简介：
- 基金信息：
- DOI：10.11907/rjdk.241486
  CLC： TP391;G647
- Received：28 May 2024，
  
  Published：15 September 2025
- 稿件说明：
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刘哲,单剑锋,杨立军.基于CCSS十年追踪调查的学生留言文本分析[J].软件导刊,2025,24(09):34-40.

LIU Zhe,SHAN Jianfeng,YANG Lijun.Text Analysis of Student Message Based on CCSS Ten-year Follow-up Survey[J].Software Guide,2025,24(09):34-40.
刘哲,单剑锋,杨立军.基于CCSS十年追踪调查的学生留言文本分析[J].软件导刊,2025,24(09):34-40. DOI： 10.11907/rjdk.241486.

LIU Zhe,SHAN Jianfeng,YANG Lijun.Text Analysis of Student Message Based on CCSS Ten-year Follow-up Survey[J].Software Guide,2025,24(09):34-40. DOI： 10.11907/rjdk.241486.

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