Scaled Properties and FastRP Embeddings

CentralityHow important a node is within a graph. Each centrality algorithm defines importance differently. and community detectionA family of algorithms that group nodes by how they connect. Each algorithm defines a community differently. reveal graph propertiesA named value stored on a node or a relationship.. EmbeddingsInformation represented as a numerical vector, positioned so that similar information sits close together. encode them into vectors for machine learning.

In this lesson, you'll scale features, create embeddings with FastRPA node embedding algorithm, short for Fast Random Projection. It builds each node's vector by combining random vectors drawn from the nodes around it., and cluster papers to compare with official subject labelsA tag on a node that groups it with other nodes of the same kind. A node can carry more than one..