Graph embedding

Technique used to represent graph-structured data in a continuous vector space, preserving the graph's structural properties. It includes methods like DeepWalk, Node2Vec, GCNs, and GraphSAGE, and is useful for tasks such as node classification, link prediction, and graph clustering. This technique is particularly beneficial for data scientists and researchers working on complex network analysis and machine learning applications involving graph data.