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[ACL2018] Cold-Start Aware User and Product Attention for Sentiment Classification
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HCSC

Cold-Start Aware User and Product Attention for Sentiment Classification

This TensorFlow code was used in the experiments of the research paper

Reinald Kim Amplayo, Jihyeok Kim, Sua Sung, and Seung-won Hwang. Cold-Start Aware User and Product Attention for Sentiment Classification. ACL, 2018.

You will need to download the original data here: https://drive.google.com/open?id=1PxAkmPLFMnfom46FMMXkHeqIxDbA16oy

Also, if you want to use the sparse data, the data folder contains the IDs of the data instances used. Please refer to the readme file inside the data folder.

You will also need GloVe pretrained word vectors which can be downloaded here: http://nlp.stanford.edu/data/glove.840B.300d.zip

To run the code, use the following command:

python src/hcsc_main.py data_dir base_model train_type

where:

  • data_dir is the data folder (e.g. data/imdb).
  • base_model can be cnn, rnn, or hcwe. To use the full HCSC model, use hcwe.
  • train_type is the extension of the dataset filename if the sparse datasets are used (e.g. _zero2 if Sparse20 is used). If the original dataset is used, leave this argument blank

To cite the paper/code, please use this BibTex

@inproceedings{amplayo2018cold,
	Author = {Reinald Kim Amplayo and Jihyeok Kim and Sua Sung and Seung-won Hwang},
	Booktitle = {ACL},
	Location = {Melbourne, Australia},
	Year = {2018},
	Title = {Cold-Start Aware User and Product Attention for Sentiment Classification},
}

If you have questions, send me an email: rktamplayo at yonsei dot ac dot kr

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