Deep Learning on Graphs for Natural Language Processing
Lingfei Wu, Yu Chen, Heng Ji, Bang Liu
Abstract
This tutorial of Deep Learning on Graphs for Natural Language Processing (DLG4NLP) will cover relevant and interesting topics on applying deep learning on graph techniques to NLP, including automatic graph construction for NLP, graph representation learning for NLP, advanced GNN based models (e.g., graph2seq, graph2tree, and graph2graph) for NLP, and the applications of GNNs in various NLP tasks (e.g., machine translation, natural language generation, information extraction and semantic parsing). In addition, a handson demonstration session will be included to help the audience gain practical experience on applying GNNs to solve challenging NLP problems using our recently developed open source library - Graph4NLP, the first library for researchers and practitioners for easy use of GNNs for various NLP tasks.