MiaSRec

This is the official code for SIGIR 2024 paper: 'Multi-intent-aware Session-based Recommendation'.

We implemented our model based on the recommedndation framework library RecBole v1.2.0) and CORE.

Requirements

you can use the following command to install the environment

conda create -n miasrec python=3.8
conda activate miasrec
pip install -r requirements.txt

Datasets

make dataset folder and unzip $DATASET$.zip to dataset folder $DATASET$: (diginetica, retailrocket, yoochoose, dressipi, tmall, lastfm)

for DATASET in diginetica retailrocket yoochoose dressipi tmall lastfm
do
unzip $DATASET.zip -d dataset/$DATASET
done

Reproduction

python main.py --model miasrec --dataset diginetica --beta_logit 0.9
python main.py --model miasrec --dataset retailrocket --beta_logit 0.8
python main.py --model miasrec --dataset yoochoose --beta_logit 0.7
python main.py --model miasrec --dataset tmall --beta_logit 0.9
python main.py --model miasrec --dataset dressipi --beta_logit 0.9
python main.py --model miasrec --dataset lastfm --beta_logit 0.9

Citation

Please cite our papaer:

@article{choi2024multi,
  title={Multi-intent-aware Session-based Recommendation},
  author={Choi, Minjin and Kim, Hye-young and Cho, Hyunsouk and Lee, Jongwuk},
  journal={arXiv preprint arXiv:2405.00986},
  year={2024}
}