Our model CLF4SRec is implemented based on the RecBole.
Both the processing of the dataset and the metrics calculation follow the implementation of RecBole.
CLF4SRec in /recbole/model/sequential_recommender/clf4srec.py
We provide the script main_run.py to run the model
If you use this code, please cite the pape
@article{CLF4SRec,
title = {Contrastive Learning with Frequency Domain for Sequential Recommendation},
journal = {Applied Soft Computing},
pages = {110481},
year = {2023},
issn = {1568-4946},
doi = {https://doi.org/10.1016/j.asoc.2023.110481},
url = {https://www.sciencedirect.com/science/article/pii/S1568494623004994},
author = {Yichi Zhang and Guisheng Yin and Yuxin Dong and Liguo Zhang}
}