Pre-training on large-scale heterogeneous graph

• Main Authors: JIANG, Xunqiang, JIA, Tianrui, FANG, Yuan, SHI, Chuan, LIN, Zhe, WANG, Hui
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Heterogeneous graph; Self-supervised learning; Pre-training; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/6888; https://ink.library.smu.edu.sg/context/sis_research/article/7891/viewcontent/KDD21_PT_HGNN.pdf
• Institution: Singapore Management University

Graph neural networks (GNNs) emerge as the state-of-the-art representation learning methods on graphs and often rely on a large amount of labeled data to achieve satisfactory performance. Recently, in order to relieve the label scarcity issues, some works propose to pre-train GNNs in a self-supervis...