Graph Convolutional Networks for Text Classification

Understand

Text classification is an important and classical problem in natural language processing.

• There have been a number of studies that applied convolutional neural networks (convolution on regular grid, e.g., sequence) to classification.
• However, only a limited number of studies have explored the more flexible graph convolutional neural networks (convolution on non-grid, e.g., arbitrary graph) for the task.
• In this work, we propose to use graph convolutional networks for text classification.