TY - GEN
T1 - Deep Learning on Graphs for Natural Language Processing
AU - Wu, Lingfei
AU - Chen, Yu
AU - Ji, Heng
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/7/11
Y1 - 2021/7/11
N2 - 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.
AB - 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.
KW - deep learning
KW - graph learning
KW - graph neural network
KW - natural language processing
UR - http://www.scopus.com/inward/record.url?scp=85111693660&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85111693660&partnerID=8YFLogxK
U2 - 10.1145/3404835.3462809
DO - 10.1145/3404835.3462809
M3 - Conference contribution
AN - SCOPUS:85111693660
T3 - SIGIR 2021 - Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
SP - 2651
EP - 2653
BT - SIGIR 2021 - Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
PB - Association for Computing Machinery
T2 - 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2021
Y2 - 11 July 2021 through 15 July 2021
ER -