Network Embedding

Network embedding, or network representation learning, refers to the technique of mapping nodes in a graph to real-valued vectors in a multi-dimensional space. The core objective is to preserve the structural characteristics of the graph so that the embedded vectors can accurately reflect the relationships between nodes. These vectors can be used as inputs for network and graph analysis tasks such as link prediction, enhancing the performance and interpretability of the models.