Link prediction consists of guessing which unknown connections between existing nodes in the graph are more likely to be real, now or in the future. With a proper formulation, this can be turned into a machine learning problem. But before trying to build a model for link prediction, as for any data science task, we must start with a deep understanding of the problem. That will be our goal in this section. First, by using the context of dynamic graphs, we will define what exactly is hidden behind link prediction. We will also review some applications, from marketing to science.
Dynamic graphs
So far in this book, we have studied graphs in a static manner; in other words, we imported graphs from an external data source and the graph content (nodes or relationships) was never changed. Studying the graph structure in this way gives us some information about the data it is representing. However, in a real-life scenario, whether your graph models a road network or an...
