A graph neural network based framework to do the basket recommendation. Our paper is
Liu, Zhiwei, et al. "BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network." Proceedings of the 2020 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics, 2020.
Part of the instacart dataset is given in this repo. We have three files:
trainu2b.txt:
Each row isuser_id, basket_id, basket_id, ...trainb2i.txt:
Each row isbaset_id, item_id, item_id, ...testb2i.txt:
Each row isbaset_id, item_id, item_id, ...
The original data we use in the paper is too big to upload. You may find complete dataset of instacart here
Run the code under ./basConv/ folder with script:
python basConv.py --dataset inscart_1 --regs [1e-4] --alg_type basconv --embed_size 64 --layer_size [64,64] --lr 0.0002 --save_flag 1 --pretrain -1 --batch_size 4096 --epoch 2000 --verbose 50 --node_dropout_flag 0 --mess_dropout [0.2,0.2]
More info regarding the arguements, please refer to the ./basConv/parser.py file.
Python = 3.6
Tensorflow = 1.8+
Numpy, Scipy, scikit-learn should be installed accordingly.
@inproceedings{liu2020basconv,
title={BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network},
author={Liu, Zhiwei and Wan, Mengting and Guo, Stephen and Achan, Kannan and Yu, Philip S},
booktitle={Proceedings of the 2020 SIAM International Conference on Data Mining},
pages={64--72},
year={2020},
organization={SIAM}
}
We reuse some part of the code in Neural Graph Collaborative Filtering https://github.com/xiangwang1223/neural_graph_collaborative_filtering