/AMID

The code for WWW2024 paper "Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions".

Primary LanguagePython

AMID

The code for WWW2024 paper "Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions".

Train/Eval

bash run.sh

Dataset

Due to company file transfer restrictions, we have uploaded the processed dataset files, including the sampled "MYbank-CDR" dataset.

If you want to generate your own CDSR dataset, please refer file amazon_dataset/filter_DR_dataset.py and repository-NMCDR.

Citation

If you found the codes are useful, please cite our paper.

  @inproceedings{xu2024rethinking,
  title = {Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions},
  author = {Wujiang Xu, Qitian Wu, Runzhong Wang, Mingming Ha, Qiongxu Ma, Linxun Chen, Bing Han, Junchi Yan},
  booktitle = {The Web Conference (WWW)},
  year = {2024}
  }

Contact us

Please feel free to contact us with the email to W. Xu "wujiang dot xu at rutgers dot edu" or "swustimp at gmail dot com".