Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks
Table 2: Comparison results of different methods on laptop and restaurant datasets. Numbers in parentheses indicate number of layers in our model.
['[EMPTY]', 'Laptop', 'Restaurant']
With GloVe embeddings, our approach TD-GAT-GloVe (k), where k is the number of layers, outperforms all these previous methods. Among these baselines, Feature-based SVM achieves strong performance on this task, which indicates the importance of feature engineering and syntax knowledge.