Graph Embeddings

Algorithms for generating vector representations of graph elements.

Overview

Graph embeddings convert nodes, edges, or entire graphs into fixed-dimensional vectors that can be used for:

• Machine Learning: Feed embeddings into ML models for classification, clustering, or prediction
• Similarity Search: Find similar nodes using vector distance metrics
• Visualization: Project high-dimensional graph structure to 2D/3D
• Link Prediction: Predict missing edges based on embedding similarity

Fast Random Projection (FastRP)

FastRP is a scalable algorithm for generating node embeddings: