Contrastive Self-supervised Sequential Recommendation with Robust Augmentation
Source code for paper: Contrastive Self-supervised Sequential Recommendation with Robust Augmentation
Model architecture:
Data Augmentations:
Please cite our paper if you use this code.
@article{liu2021contrastive,
title={Contrastive self-supervised sequential recommendation with robust augmentation},
author={Liu, Zhiwei and Chen, Yongjun and Li, Jia and Yu, Philip S and McAuley, Julian and Xiong, Caiming},
journal={arXiv preprint arXiv:2108.06479},
year={2021}
}
Python >= 3.7
Pytorch >= 1.2.0
tqdm == 4.26.0
Four prepared datasets are included in data
folder.
To train our model on Sports_and_Outdoors
dataset, change to the src
folder and run following command:
python main.py --data_name Sports_and_Outdoors
- Transformer and training pipeline are implemented based on S3-Rec. Thanks them for providing efficient implementation.