Node Embedding Algorithms
Node embeddings are vector representations of properties of vertices in a graph. These vectors can be used for machine learning.
The TigerGraph Graph Data Science Library provides the following node embedding algorithms:
NodePiece is a highly scalable node embedding technique. It is implemented in the pyTigerGraph library. Using it requires a few additional steps, but it is our most scalable offering.
Weisfeiler-Lehman isomorphism has been moved to the Classification category.
Node2Vec has been retired (as of v3.9.2) because it did not meet our standards for efficiency and scalability of memory usage. Fast Random Projection is a better alternative.