Skip to content

The source code of NRCGI (Non-Recursive Cluster-Scale Graph Interacted Model for Click-Through Rate Prediction, CIKM2023).

License

Notifications You must be signed in to change notification settings

YuanchenBei/NRCGI

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

9 Commits
 
 
 
 
 
 
 
 

Repository files navigation

NRCGI

This is the Pytorch-version code of NRCGI (Non-Recursive Cluster-Scale Graph Interacted Model for Click-Through Rate Prediction, CIKM2023).

Requirements

python >= 3.8

pytorch == 1.9.1

pickle == 0.7.5

scikit-learn == 0.24.2

pandas == 1.3.3

numpy == 1.21.2

tqdm == 4.62.2

Folder Content

Usage

The below running way is based on you have entered the model folder and the datasets have been downloaded and placed on ./data.

  • We provide a running script file run.sh in model folder, which can run directly in bash.
bash run.sh
  • You can also run a single dataset we provided directly.

For MovieLens dataset, you can use the following run command:

python main.py --model_name nrcgi --dataset_name ml-10m --learning_rate 0.005 --weight_decay 0.0004

For the Amazon-Electronics dataset, you can use the following run command:

python main.py --model_name nrcgi --dataset_name electronics --learning_rate 0.005 --weight_decay 0.00005

Citation

@inproceedings{bei2023non,
  title={Non-Recursive Cluster-Scale Graph Interacted Model for Click-Through Rate Prediction},
  author={Bei, Yuanchen and Chen, Hao and Chen, Shengyuan and Huang, Xiao and Zhou, Sheng and Huang, Feiran},
  booktitle={Proceedings of the 32nd ACM International Conference on Information and Knowledge Management},
  pages={3748--3752},
  year={2023}
}

About

The source code of NRCGI (Non-Recursive Cluster-Scale Graph Interacted Model for Click-Through Rate Prediction, CIKM2023).

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published