Graph Mining

Graph mining focuses on extracting valuable information and patterns from graph-structured data, aiming to understand complex relationships between entities. Current research emphasizes developing advanced graph neural networks (GNNs) for tasks like node classification, clustering, and link prediction, often incorporating techniques like contrastive learning and modularity maximization to improve accuracy and scalability, particularly in scenarios with limited data. These advancements have significant implications across diverse fields, including cybersecurity, biomedicine, and social network analysis, enabling more effective anomaly detection, personalized recommendations, and improved understanding of complex systems.