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DisenQNet: Disentangled Representation Learning for Educational Questions

Source code and dataset for paper DisenQNet: Disentangled Representation Learning for Educational Questions.

Dependencies

  • python >= 3.6

  • gensim

  • numpy

  • torch

Usage

Train and test model

python3 src/main.py

For more running arguments, please refer to src/main.py.

Citation

If you find our work helpful, please consider citing our paper.

@inproceedings{huang2021disenqnet,
  title={DisenQNet: Disentangled Representation Learning for Educational Questions},
  author={Huang, Zhenya and Lin, Xin and Wang, Hao and Liu, Qi and Chen, Enhong and Ma, Jianhui and Su, Yu and Tong, Wei},
  booktitle={Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery \& Data Mining},
  pages={696--704},
  year={2021}
}

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  • Python 100.0%