Keywords: aspect-based sentiment classification, graph convolutional networks, dual contrastive learning, syntax label enhancement, bidirectional encoder representations from transformers (BERT) ...

Graph Convolutional Networks (GCNs) have been widely studied for attribute graph data learning. In many applications, graph node attributes/features may contain various kinds of noises, such as gross ...

Graph Auto-Encoders (GAEs) are end-to-end trainable neural network models for unsupervised learning, clustering and link prediction on graphs. GAEs are based on Graph Convolutional Networks (GCNs), a ...

Pinterest today shared details about how it created PinSage, a graph convolutional network that can learn about things like nearby Pins, or nodes, in massive web-scale graphs.

Aspect-Based Sentiment Analysis (ABSA) is a subtask of sentiment categorization that aims at mining the sentiment polarity of a given sentiment aspect in a sentence. Much of the recent research has ...