Graph Algorithms for Data Science

9 Node embeddings and classification

This chapter covers

• Introducing node embedding models
• Presenting the difference between transductive and inductive models
• Examining the difference between structural roles and homophily-based embeddings
• Introducing the node2vec algorithm
• Using node2vec embeddings in a downstream machine learning task

In the previous chapter, you used a vector to represent each node in the network. The vectors were handcrafted based on the features you deemed essential. In this chapter, you will learn how to automatically generate node representation vectors using a node embedding model. Node embedding models fall under the dimensionality reduction category.

An example of feature engineering and dimensionality reduction ...