Datasets:
Update README.md to include detailed dataset description, related papers, and remove Hugging Face upload instructions.
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README.md
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# Student Memory Logs Dataset
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This dataset contains student memory logs
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## Dataset Files
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- `opensource_dataset_forgetting_curve.tsv`: Forgetting curve data
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- `opensource_dataset_offset.tsv`: Offset-related data
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## Uploading to Hugging Face
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### Prerequisites
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1. Install required dependencies:
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```bash
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pip install -r requirements.txt
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```
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2. Login to Hugging Face (if not already logged in):
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```bash
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huggingface-cli login
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```
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### Upload Dataset
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Run the upload script with your Hugging Face repository ID:
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```bash
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python upload_to_hf.py --repo-id <your-username>/student-memory-logs
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```
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For a private repository:
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```bash
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python upload_to_hf.py --repo-id <your-username>/student-memory-logs --private
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```
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If you need to use a specific token:
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```bash
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python upload_to_hf.py --repo-id <your-username>/student-memory-logs --token <your-token>
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```
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## License
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This dataset is licensed under CC-BY-NC-4.0 (Creative Commons Attribution-NonCommercial 4.0 International).
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# Student Memory Logs Dataset
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This dataset contains the 220 million MaiMemo student memory behavior logs used in experiments by Junyao Ye, Jingyong Su, & Yilong Cao (2022). For more details and replication source code, visit: https://github.com/maimemo/SSP-MMC and https://github.com/maimemo/SSP-MMC-Plus.
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Related papers:
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- Junyao Ye, Jingyong Su, and Yilong Cao. 2022. A Stochastic Shortest Path Algorithm for Optimizing Spaced Repetition Scheduling. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. ACM, 4381–4390.doi: 10.1145/3534678.3539081
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- J. Su, J. Ye, L. Nie, Y. Cao and Y. Chen, "Optimizing Spaced Repetition Schedule by Capturing the Dynamics of Memory," in IEEE Transactions on Knowledge and Data Engineering. doi 10.1109/TKDE.2023.3251721
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## Dataset Files
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- `opensource_dataset_forgetting_curve.tsv`: Forgetting curve data
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- `opensource_dataset_offset.tsv`: Offset-related data
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## License
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This dataset is licensed under CC-BY-NC-4.0 (Creative Commons Attribution-NonCommercial 4.0 International).
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