Node Classification

Node classification aims to assign labels to nodes within a graph based on their features and relationships with other nodes. Current research heavily utilizes Graph Neural Networks (GNNs), including variations like Graph Convolutional Networks (GCNs) and Graph Attention Networks (GATs), often incorporating techniques to address challenges like oversmoothing and heterophily. Focus areas include improving robustness to noisy data and adversarial attacks, enhancing efficiency for large-scale graphs, and developing methods for few-shot and open-world scenarios. These advancements have significant implications for various applications, such as social network analysis, recommendation systems, and biological network modeling.