The source code for "Global Context Enhanced Graph Neural Network for Session-based Recommendation".

Last update: Dec 28, 2022

Related tags

Overview

GCE-GNN

Code

This is the source code for SIGIR 2020 Paper: Global Context Enhanced Graph Neural Networks for Session-based Recommendation.

Requirements

Python 3
PyTorch >= 1.3.0
tqdm

Usage

Data preprocessing:

The code for data preprocessing can refer to SR-GNN.

Train and evaluate the model:

python build_graph.py --dataset diginetica --sample_num 12
python main.py --dataset diginetica

Citation

@inproceedings{wang2020global,
    title={Global Context Enhanced Graph Neural Networks for Session-based Recommendation},
    author={Wang, Ziyang and Wei, Wei and Cong, Gao and Li, Xiao-Li and Mao, Xian-Ling and Qiu, Minghui},
    booktitle={Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval},
    pages={169--178},
    year={2020}
}

Owner

GitHub Repository

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The source code for "Global Context Enhanced Graph Neural Network for Session-based Recommendation".

Related tags

Overview

GCE-GNN

Code

Requirements

Usage

Citation

Owner

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