Building a movie RecSys
One of the most popular applications of GNNs is RecSys. If you think about the foundation of Word2Vec (and, thus, DeepWalk and Node2Vec), the goal is to produce vectors with the ability to measure their similarity. Encode movies instead of words, and you can suddenly ask for movies that are the most similar to a given input title. It sounds a lot like a RecSys, right?
But how to encode movies? We want to create (biased) random walks of movies, but this requires a graph dataset where similar movies are connected to each other. This is not easy to find.
Another approach is to look at user ratings. There are different techniques to build a graph based on ratings: bipartite graphs, edges based on pointwise mutual information, and so on. In this section, we’ll implement a simple and intuitive approach: movies that are liked by the same users are connected. We’ll then use this graph to learn movie embeddings using Node2Vec:
- First, let&...
