Aspect-level sentiment classification is a hot research topic in natural language processing (NLP). One of the key challenges is that how to develop effective algorithms to model the relationships between aspects and opinion words appeared in a sentence. Among the various methods proposed in the literature, the graph convolutional networks (GCNs) achieve the promising results due to their good ability to capture the long distance between the aspects and the opinion words. However, the existing methods cannot effectively leverage the edge information of dependency parsing tree, resulting in the...
