Tensor Graph Convolutional Networks for Text Classification

Understand

Compared to sequential learning models, graph-based neural networks exhibit some excellent properties, such as ability capturing global information.

• In this paper, we investigate graph-based neural networks for text classification problem.
• A new framework TensorGCN (tensor graph convolutional networks), is presented for this task.
• A text graph tensor is firstly constructed to describe semantic, syntactic, and sequential contextual information.