How to Create Representations of Entities in a Knowledge Graph using pyRDF2Vec

Graphs are data structures that are useful to represent ubiquitous phenomena, such as social networks, chemical molecules and recommendation systems. One of their strengths lies in the fact that they explicitly model relations (i.e. We can illustrate the added value of this data enrichment using the Cora citation network. This dataset contains a bag-of-words representation for a few hundred papers and the citation relations between each of these papers. If we apply dimensionality reduction (t-SNE) to create a 2D plot of the bag-of-words representations (Figure 1, left), we can see clusters (they are colored according to their research topic) arise but they overlap.