Structural Node Embedding

Structural Node Embedding is a graph embedding technique that aims to map nodes in a graph to a low-dimensional vector space while preserving the structural relationships between nodes. This method learns structural representations of nodes, effectively capturing their positions and roles within the network, thereby providing precise vector representations for target nodes. In fields such as social network analysis, recommendation systems, and bioinformatics, Structural Node Embedding can significantly enhance the performance of graph data mining and machine learning tasks, improving the predictive power and interpretability of models.