/LatentLinearCritiquingforConvRecSys

Official Code Framework of the paper "Latent Linear Critiquing for Conversational Recommender Systems"

Primary LanguagePython

LatentLinearCritiquingforConvRecSys

If you are interested in building up your research on this work, please cite:

@inproceedings{sanner:www20,
  author = {Kai Luo and Scott Sanner and Ga Wu and Hanze Li and Hojin Yang},
  title = {Latent Linear Critiquing for Conversational Recommender Systems},
  year = {2020},
  booktitle = {Proceedings of the 29th International Conference on the World Wide Web (WWW-20)},
  address = {Taipei, Taiwan},
  url_paper = {https://ssanner.github.io/papers/www20_llc.pdf}
}

Author Affiliate

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Algorithm Implemented

  1. LP Option1
  2. LP Option2
  3. LP Option3

Dataset

  1. Amazon CDs&Vinyl,
  2. Beer Advocate,

We don't have rights to release the datasets. Please ask permission from Professor Julian McAuley.

Please refer to the preprocess folder for preprocessing raw datasets steps.

Keyphrase

Keyphrases we used are not necessarily the best. If you are interested in how we extracted those keyphrases, please refer to the preprocess folder. If you are interested in what keyphrases we extracted, please refer to the data folder.

Example Commands

Reproduce Critiquing

python reproduce_critiquing.py --data_dir "data/beer/" --dataset_name beer/ --save_path beer/critiquing_results.csv --num_users_sampled 10 --critiquing_model_name LP1Simplified