TiSASRec.paddle
A PaddlePaddle implementation of Time Interval Aware Self-Attentive Sequential Recommendation.
Introduction
论文：Time Interval Aware Self-Attentive Sequential Recommendation
Results
| Datasets | Metrics | Paper’s | Ours | abs. improv. |
|---|---|---|---|---|
| MovieLens-1m | HIT@10 | 0.8038 | 0.8050 | 0.0012 |
| MovieLens-1m | NDCG@10 | 0.5706 | 0.5752 | 0.0046 |
Requirement
- Python >= 3
- PaddlePaddle >= 2.0.0
- see
requirements.txt
Dataset
MovieLens-1m (max_len = 50)
Usage
Train
bash ./script/train.sh
模型在 200 epochs 左右收敛，日志见 nohup.out。
Test
bash ./script/eval.sh
可以得到如下结果：
References
@inproceedings{li2020time,
title={Time Interval Aware Self-Attention for Sequential Recommendation},
author={Li, Jiacheng and Wang, Yujie and McAuley, Julian},
booktitle={Proceedings of the 13th International Conference on Web Search and Data Mining},
pages={322--330},
year={2020}
}
- https://github.com/JiachengLi1995/TiSASRec
- https://github.com/pmixer/TiSASRec.pytorch
- https://github.com/paddorch/SASRec.paddle
