Paper - [ArXiv]
- CaDRec: Contextualized and Debiased Recommender Model., SIGIR 2024 Oral.
- Xinfeng Wang, Fumiyo Fukumoto, Jin Cui, Yoshimi Suzuki, Jiyi Li, Dongjin Yu.
python Main.py
- Configures are given by Constants.py and Main.py
- If you have any problem, please feel free to contact me at kaysenn@163.com.
pip install -r requirement.txt
Three files are required: train.txt (for training), tune.txt (for tuning), and test.txt (for testing).
Each line denotes an interaction including a user interacted with at times.
The format is [#USER_ID]\t[#ITEM_ID]\t[#TIMES]\n, which is the same for all files.
For example,
0 0 1
0 1 3
0 3 2
1 2 1
the user (ID=0) visited the item (ID=0) at 1 time,
the item (ID=1) at 3 times,
and the item (ID=3) at 2 times.
the user (ID=1) visited the item (ID=2) at 1 time.
If this repository helps you, please cite:
@inproceedings{wang2023cadrec,
title={CaDRec: Contextualized and Debiased Recommender Model},
author={Wang, Xinfeng and Fukumoto, Fumiyo and Cui, Jin and Suzuki, Yoshimi and Li, Jiyi and Yu, Dongjin},
booktitle={Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval},
pages={405–-415},
year={2024}
}