Target Graph

Target graph analysis focuses on understanding and manipulating relationships within a target graph structure, encompassing tasks like subgraph matching, graph generation, and attack detection against graph neural networks (GNNs). Current research emphasizes developing efficient algorithms, such as diffusion-based methods for hypergraph generation and reinforcement learning-based approaches for subgraph search, to address the computational challenges posed by large and complex graphs. These advancements have significant implications for various fields, including social network analysis, bioinformatics, and improving the robustness and security of GNN-based applications.