Link prediction — inferring missing or future edges in a graph — underpins knowledge graph completion, drug-target discovery, and social network recommendation. TransE (2013) launched the knowledge graph embedding era, and the field matured through DistMult, RotatE, and CompGCN, benchmarked on FB15k-237 and WN18RR. The current frontier is inductive link prediction (generalizing to unseen entities), where GNN-based methods like NBFNet and foundation models like ULTRA (2024) show that a single model can transfer across entirely different knowledge graphs without retraining.
Author collaboration network from MAG. Predict future collaborations from past collaborations. 235K nodes, 1.2M edges. Standard OGB link-prediction benchmark, evaluated by Hits@50.
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