KID-22 / DDFM

The official implementation of the CIKM2023 paper “Dually Enhanced Delayed Feedback Modeling for Streaming Conversion Rate Prediction"

Code for paper of CIKM 2023: Dually Enhanced Delayed Feedback Modeling for Streaming Conversion Rate Prediction [PDF]

Quick Start

1. Please run the shell file run_pretrain.sh to get the pretrain model.

2. Please run the shell file run_stream.sh to evaluate our method DDFM in the streaming protocol.

Environment

Our experimental environment is shown below:

numpy version: 1.19.2
pandas version: 1.1.5
scikit-learn version: 0.24.2
torch version: 1.7.0+cu110
torchvision version: 0.8.1+cu110

Reference

Our experiments follow the previous studies: [ES-DFM], [DEFER], [DEFUSE].

Citation

If you find our code or work useful for your research, please cite our work.

@inproceedings{dai2023dually,
  title={Dually Enhanced Delayed Feedback Modeling for Streaming Conversion Rate Prediction},
  author={Dai, Sunhao and Zhou, Yuqi and Xu, Jun and Wen, Ji-Rong},
  booktitle={Proceedings of the 32nd ACM International Conference on Information and Knowledge Management},
  pages={390--399},
  year={2023}
}