A Gentle Introduction to Graph Neural Network (Basics, DeepWalk, and GraphSage)

Recently, Graph Neural Network (GNN) has gained increasing popularity in various domains, including social network, knowledge graph, recommender system, and even life science. The power of GNN in modeling the dependencies between nodes in a graph enables the breakthrough in the research area related to graph analysis. This article aims to introduce the basics of Graph Neural Network and two more advanced algorithms, DeepWalk and GraphSage. Before we get into GNN, let's first understand what is Graph. In Computer Science, a graph is a data structure consisting of two components, vertices and edges. A graph G can be well described by the set of vertices V and edges E it contains.