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 becnn
,rnn
, orhcwe
. To use the full HCSC model, usehcwe
.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