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Code for the RecSys'20 paper "TAFA: Two-headed Attention Fused Autoencoder for Context-Aware Recommendations"

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RecSys'20 TAFA: Two-headed Attention Fused Autoencoder for Context-Aware Recommendations

Authors: Jinpeng Zhou*, Zhaoyue Cheng*, Felipe Perez, Maksims Volkovs
[paper]

The code was developed and tested on the following python environment:

python 3.7.6
pytorch 1.4.0
pandas 1.1.0
tqdm
allennlp
gensim
cupy
nltk

To train and eveluate TAFA on the Amazon datasets (digital music, grocery and gourmet food, video games, cds and vinyl), run this command:

sh run_amazon.sh [digital_music|grocery_and_gourmet_food|video_games|cds_and_vinyl]

If you find this code useful in your research, please cite the following paper:

@inproceedings{zhou2020tafa,
  title={TAFA: {Two-headed} Attention Fused Autoencoder for Context-Aware Recommendations},
  author={Jinpeng Zhou, Zhaoyue Cheng, Felipe Perez, Maksims Volkovs},
  booktitle={RecSys},
  year={2020}
}

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Code for the RecSys'20 paper "TAFA: Two-headed Attention Fused Autoencoder for Context-Aware Recommendations"

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