Introducing Node2Vec
Node2Vec was introduced in 2016 by Grover and Leskovec from Stanford University [1]. It keeps the same two main components from DeepWalk: random walks and Word2Vec. The difference is that instead of obtaining sequences of nodes with a uniform distribution, the random walks are carefully biased in Node2Vec. We will see why these biased random walks perform better and how to implement them in the two following sections:
- Defining a neighborhood
- Introducing biases in random walks
Let’s start by questioning our intuitive concept of neighborhoods.
Defining a neighborhood
How do you define the neighborhood of a node? The key concept introduced in Node2Vec is the flexible notion of a neighborhood. Intuitively, we think of it as something close to the initial node, but what does “close” mean in the context of a graph? Let’s take the following graph as an example:
Figure 4.1 – Example...
