Predicting Links with Graph Neural Networks
Link prediction is one of the most popular tasks performed with graphs. It is defined as the problem of predicting the existence of a link between two nodes. This ability is at the core of social networks and recommender systems. A good example is how social media networks display friends and followers you have in common with others. Intuitively, if this number is high, you are more likely to connect with these people. This likelihood is precisely what link prediction tries to estimate.
In this chapter, we will first see how to perform link prediction without any machine learning. These traditional techniques are essential to understanding what GNNs learn. We will then refer to previous chapters about DeepWalk and Node2Vec to link prediction through matrix factorization. Unfortunately, these techniques have significant limitations, which is why we will transition to GNN-based methods.
We will explore three methods from two different...
