- Lei Li, Yongfeng Zhang, Li Chen. Personalized Prompt Learning for Explainable Recommendation. ACM Transactions on Information Systems (TOIS), 2023.
A T5 version that can perform multiple recommendation tasks is available at POD!
A small unpretrained Transformer version is available at PETER!
A small ecosystem for Recommender Systems-based Natural Language Generation is available at NLG4RS!
Datasets to download
- TripAdvisor Hong Kong
- Amazon Movies & TV
- Yelp 2019
For those who are interested in how to obtain (feature, opinion, template, sentiment) quadruples, please refer to Sentires-Guide.
Below are examples of how to run PEPLER (continuous prompt, discrete prompt, MF regularization and MLP regularization).
python -u main.py \
--data_path ../TripAdvisor/reviews.pickle \
--index_dir ../TripAdvisor/1/ \
--cuda \
--checkpoint ./tripadvisor/ >> tripadvisor.log
python -u discrete.py \
--data_path ../TripAdvisor/reviews.pickle \
--index_dir ../TripAdvisor/1/ \
--cuda \
--checkpoint ./tripadvisord/ >> tripadvisord.log
python -u reg.py \
--data_path ../TripAdvisor/reviews.pickle \
--index_dir ../TripAdvisor/1/ \
--cuda \
--use_mf \
--checkpoint ./tripadvisormf/ >> tripadvisormf.log
python -u reg.py \
--data_path ../TripAdvisor/reviews.pickle \
--index_dir ../TripAdvisor/1/ \
--cuda \
--rating_reg 1 \
--checkpoint ./tripadvisormlp/ >> tripadvisormlp.log
- Python 3.6
- PyTorch 1.6
- transformers 4.18.0
@article{TOIS23-PEPLER,
title={Personalized Prompt Learning for Explainable Recommendation},
author={Li, Lei and Zhang, Yongfeng and Chen, Li},
journal={ACM Transactions on Information Systems (TOIS)},
year={2023}
}