本研究利用jieba、TF-IDF 及國家雙語詞彙資料集，前端運用html、css、javascript設計響應式網頁(RWD)，後端以python、php和資料庫(MySQL)連動來建立系統。 參照108課綱，對學生之備審資料進行自然語言處理(NLP)等分析，並透過轉換之數據找出學生特長、提供教授提問方向的建議，除了能提供學生修改建議，也能有效節省教授閱覽繁多資料的時間並快速找出學生亮點。
active 2024-09-29 → 2024-09-29 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2024-09-29 to 2024-09-29. Pushes: 2 total, peak 2 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
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- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| CodingShih | 2 | 2 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.