yixianqianzy/CoPD

The implemention code of our paper titled 'Consistency-guided Preference Disentanglement for Cross-domain Recommendations'

CoPD-master

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This is a pytorch implementation of our paper: "Consistency-guided Preference Disentanglement of Cross Domain Recommendation"

Requirements:

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python=3.9.0

pytorch=1.12.0

numpy=1.24.3

scipy=1.10.1

Runing commands

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Firstly, cd src. Next, run the codes with the following commands on different scenarios.

-->on Elec & Phone:

CUDA_VISIBLE_DEVICES=0 python train_rec.py --dataset electronic_phone --lambda1 1 --lambda2 1 

-->on Sport & Cloth:

CUDA_VISIBLE_DEVICES=0 python train_rec.py --dataset sport_cloth --lambda1 1 --lambda2 1 

-->on Sport & Phone:

CUDA_VISIBLE_DEVICES=0 python train_rec.py --dataset sport_phone --lambda1 0.01 --lambda2 1

-->on Elec & Cloth:

CUDA_VISIBLE_DEVICES=0 python train_rec.py --dataset electronic_cloth --lambda1 0.01 --lambda2 1

If you find this paper or codes useful, please cite our paper. Thank you!

Acknowledgement

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This code refers code from:

https://github.com/HKUDS/LightGCL

https://github.com/cjx96/DisenCDR

https://github.com/xuChenSJTU/ETL-master

We thank the authors for sharing their codes!