Introduction

Contrastive Self-supervised Sequential Recommendation with Robust Augmentation

Source code for paper: Contrastive Self-supervised Sequential Recommendation with Robust Augmentation

Model architecture:

Data Augmentations:

Reference

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}
}

Implementation

Requirements

Python >= 3.7
Pytorch >= 1.2.0
tqdm == 4.26.0

Datasets

Four prepared datasets are included in data folder.

Train Model

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

Acknowledgement

• Transformer and training pipeline are implemented based on S3-Rec. Thanks them for providing efficient implementation.