bopeng112 / ham

The HAM models for Sequential Recommendation

The pytorch implementation of the paper:

HAM: Hybrid Associations Models for Sequential Recommendation Arxiv: https://arxiv.org/pdf/2002.11890.pdf

Author: Bo Peng ([email protected])

Feel free to send me an email if you have any questions.

Environments

• python 3.7.3
• PyTorch (version: 1.2.0)
• numpy (version: 1.16.2)
• scipy (version: 1.2.1)
• sklearn (version: 0.20.3)

Dataset and Data preprocessing

Please refer to our paper for the details of datasets and the preprocessing procedure. we upload the CDs and ML-1M datasets for the seek of reproducibility. Please feel free to contact me if you need more preprocessed data.

Example

Please refer to the following example on how to train and evaluate the model (you are recommended to run the code using GPUs).

python run.py --data=CDs --n_iter=300 --L=5 --T=3 --d=400 --model=xHAM --neg_samples=3 --P=2 --isTrain=0 --setting=CUT --l2=1e-3 --order=2

Acknowledgment

The training framework is primarily built on HGN. Thanks for the great work!