Advancement in graph data mining: applications in unsupervised, continual, and few-shot learning

• Main Author: Rakaraddi, Appan
• Other Authors: Lam Siew Kei
• Format: Thesis-Doctor of Philosophy
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Computer and Information Science; Graph neural networks; Continual learning; Few-shot learning
• Online Access: https://hdl.handle.net/10356/176227
• Institution: Nanyang Technological University

Graph mining has proven to be extremely useful in analysing features and properties of real-world graphs. This enables a number of tasks including the prediction and evaluation of how information varies with changes in the link structure, generating and building models to extract properties such as...