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Set-To-Arrangment Ranking (STARank)



This is a pytorch implementation STARank model. This is the experiment code in the following work:

Replace Scoring with Arrangement: A Contextual Set-to-Arrangement Framework for Learning-to-Rank
Jiarui Jin, Xianyu Chen, Weinan Zhang, Mengyue Yang, Yang Wang, Yali Du, Yong Yu, Jun Wang.
CIKM 2023

Prerequisites

  • Python 3.6
  • Pytorch 1.8.0

References

If you find this work helpful in your research, please consider citing the following paper. The bibtex are listed below:

@inproceedings{jin2020efficient,
  title={Replace Scoring with Arrangement: A Contextual Set-to-Arrangement Framework for Learning-to-Rank},
  author={Jin, Jiarui and Chen, Xianyu and Zhang, Weinan and Yang, Mengyue and Wang, Yang and Du, Yali and Yu, Yong and Wang, Jun},
  booktitle={Proceedings of the 32nd ACM International Conference on Information \& Knowledge Management},
  year={2023}
}

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