Text-attributed graph representation learning : Methods, applications, and challenges

• Main Authors: ZHANG, Ce, YANG, Menglin, YING, Rex, LAUW, Hady Wirawan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Document representation learning; Graph algorithms; Neural networks; Pre-trained Language Models; Topic models; Text mining; Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/9841; https://ink.library.smu.edu.sg/context/sis_research/article/10841/viewcontent/webconf24tut.pdf
• Institution: Singapore Management University

Text documents are usually connected in a graph structure, resulting in an important class of data named text-attributed graph, e.g., paper citation graph and Web page hyperlink graph. On the one hand, Graph Neural Networks (GNNs) consider text in each document as general vertex attribute and do not...