Link Prediction

A task aimed at predicting edges that are not currently present in a graph but are likely to exist.

Link prediction is one of the most important tasks in graph learning and aims to infer missing or future relationships. Social recommendations, knowledge graph completion, drug-target interaction modeling, and fraud-network analysis are all examples of this task. GNNs can model these relationships more effectively through learned node representations. The semantic content of graph structure plays a decisive role here.