/ComparER

Code of the paper "Explainable Recommendation with Comparative Constraints on Product Aspects", WSDM'21

Primary LanguagePython

Explainable Recommendation with Comparative Constraints on Product Aspects

This is the code for the paper:

Explainable Recommendation with Comparative Constraints on Product Aspects
Trung-Hoang Le and Hady W. Lauw
Presented at WSDM 2021

If you find the code and data useful in your research, please cite:

@inproceedings{10.1145/3437963.3441754,
  title     = {Explainable Recommendation with Comparative Constraints on Product Aspects},
  author    = {Le, Trung-Hoang and Lauw, Hady W.},
  year      = {2021},
  isbn      = {9781450382977},
  publisher = {Association for Computing Machinery},
  address   = {New York, NY, USA},
  url       = {https://doi.org/10.1145/3437963.3441754},
  doi       = {10.1145/3437963.3441754},
  booktitle = {Proceedings of the 14th ACM International Conference on Web Search and Data Mining},
  pages     = {967–975},
  numpages  = {9},
  keywords  = {explainable recommendation, comparative constraints},
  location  = {Virtual Event, Israel},
  series    = {WSDM '21}
}

How to run

pip install -r requirements.txt

There are two variants of ComparER model: subjective and objective.

Run ComparER on Subjective Aspect-Level Quality

Run MTER model:

python mter.py

MTER is the base model of ComparER with subjective aspect-level quality. After finish training MTER, we can continue train ComparERSub by the command:

python comparer_sub.py

Run ComparER on Objective Aspect-Level Quality

Run EFM model:

python efm.py

EFM is the base model of ComparER with objective aspect-level quality. After finish training EFM, we can continue train ComparERObj by the command:

python comparer_obj.py

Contact

Questions and discussion are welcome: lthoang.com