Edge Proposal Sets for Link Prediction

Understand

Graphs are a common model for complex relational data such as social networks and protein interactions, and such data can evolve over time (e.g., new friendships) and be noisy (e.g., unmeasured interactions).

• Link prediction aims to predict future edges or infer missing edges in the graph, and has diverse applications in recommender systems, experimental design, and complex systems.
• Even though link prediction algorithms strongly depend on the set of edges in the graph, existing approaches typically do not modify the graph topology to improve performance.
• Here, we demonstrate how simply adding a set of edges, which we call a \emph{proposal set}, to the graph as a pre-processing step can improve the performance of several link prediction algorithms.