This repository contains the code for the paper "Improving Representation Learning for Session-based Recommendation".
The code has been tested on an environment with Python 3.9.7, PyTorch 1.9.1, Numpy 1.21.2, and DGL 0.7.1.
The datasets are taken from the previous work Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation (AAAI'21). You can download the datasets in this GitHub repo and extract them to the datasets folder.
To train FOCOL, run the following command:
python run.py expts/focol/focol.py --dataset-dir datasets/digineticawhich trains FOCOL on diginetica with default hyperparameters.
You can see the detailed usage with the following command:
python run.py expts/focol/focol.py -hIf you find the code useful, please cite our [paper](https://ieeexplore.ieee.org/abstract/document/10020851):
@inproceedings{chen2022focol,
title="Improving Representation Learning for Session-based Recommendation",
author="Tianwen {Chen} and Raymond Chi-Wing {Wong}",
booktitle="IEEE International Conference on Big Data",
year="2022"
}