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Modeling Sentiment Dependencies with Graph Convolutional Networks for Aspect-level Sentiment Classification
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README.md

SDGCN

Tensorflow Implementations.

使用Tensorflow实现。

Requirement

  • python 3.6 / 3.7
  • tensorflow >= 1.12
  • numpy
  • sklearn
  • bert_embedding

Usage

Creat the embedding

  • GloVe: Download pre-trained word vectors here. In this implement, we use glove.42B.300d.zip

  • BERT: Refer to creat_BERT_embedding.py to create BERT Embedding if need.

Training

python run_glove.py 

Train model with GloVe Embedding. See run_glove.py for more training arguments.

python run_bert.py 

Train model with BERT Embedding. See run_bert.py for more training arguments.

Citation

The manuscript is avaliable in arXiv:

"Modeling Sentiment Dependencies with Graph Convolutional Networks for Aspect-level Sentiment Classification". arXiv preprint arXiv:1906.04501 (2019) [pdf]

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