Breeze-del / HEMLCODE

HEML

This is our implementation for our paper Hypergraph-Enhanced Multi-Interest Learning for Multi-Behavior Sequential Recommendation, Submitted to the ESWA.

Requirements

The code is built on Pytorch and the RecBole benchmark library. Run the following code to satisfy the requeiremnts by pip:

pip install -r requirements.txt

Datasets

Download the three public datasets we use in the paper at:

Tmall : https://tianchi.aliyun.com/dataset/140281

IJCAI : https://tianchi.aliyun.com/dataset/42

UserB : https://tianchi.aliyun.com/dataset/649

Unzip the datasets and move them to ./dataset/

Run HEML

python run_HEML.py --model=[HEML] --dataset=[tmall_beh] --gpu_id=[0] --batch_size=[2048], where [value] means the default value.

Tips

• Note that we modified the evaluation sampling setting in recbole/sampler/sampler.py to make it static.
• Feel free to explore other baseline models provided by the RecBole library and directly run them to compare the performances.