Graph Mining Task

Graph mining focuses on extracting meaningful information and patterns from graph-structured data, aiming to solve tasks like node classification, edge prediction, and recommendation. Current research heavily utilizes graph neural networks (GNNs), often enhanced by large language models (LLMs) to leverage contextual information and improve accuracy, while also addressing challenges like fairness and robustness across diverse graph types. These advancements are crucial for various applications, including social network analysis, recommendation systems, and drug discovery, where understanding complex relationships within data is paramount.