Papers › Neural Common Neighbor with Completion for Link Prediction
Neural Common Neighbor with Completion for Link Prediction
Xiyuan Wang, Haotong Yang, Muhan Zhang
In this work, we propose a novel link prediction model and further boost it by studying graph incompleteness. First, we introduce MPNN-then-SF, an innovative architecture leveraging structural feature (SF) to guide MPNN's representation pooling, with its implementation, namely Neural Common Neighbor (NCN). NCN exhibits superior expressiveness and scalability compared with existing models, which can be classified into two categories: SF-then-MPNN, augmenting MPNN's input with SF, and SF-and-MPNN, decoupling SF and MPNN. Second, we investigate the impact of graph incompleteness -- the phenomenon that some links are unobserved in the input graph -- on SF, like the common neighbor. Through dataset visualization, we observe that incompleteness reduces common neighbors and induces distribution shifts, significantly affecting model performance. To address this issue, we propose to use a link prediction model to complete the common neighbor structure. Combining this method with NCN, we propose Neural Common Neighbor with Completion (NCNC). NCN and NCNC outperform recent strong baselines by large margins, and NCNC further surpasses state-of-the-art models in standard link prediction benchmarks. Our code is available at https://github.com/GraphPKU/NeuralCommonNeighbor.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Link Property Prediction | ogbl-ddi | NeuralCommonNeighbor | Ext. data | No | #13 of 31 | Archive leaderboard | report |
| Link Property Prediction | ogbl-ddi | NeuralCommonNeighbor | Number of params | 1412098 | #13 of 31 | Archive leaderboard | report |
| Link Property Prediction | ogbl-ddi | NeuralCommonNeighbor | Test Hits@20 | 0.8232 ± 0.0610 | #13 of 31 | Archive leaderboard | report |
| Link Property Prediction | ogbl-ddi | NeuralCommonNeighbor | Validation Hits@20 | 0.7172 ± 0.0025 | #13 of 31 | Archive leaderboard | report |
| Link Property Prediction | ogbl-ppa | **Neural Common Neighbor ** | Ext. data | No | #7 of 26 | Archive leaderboard | report |
| Link Property Prediction | ogbl-ppa | **Neural Common Neighbor ** | Number of params | 33538 | #7 of 26 | Archive leaderboard | report |
| Link Property Prediction | ogbl-ppa | **Neural Common Neighbor ** | Test Hits@100 | 0.6119 ± 0.0085 | #7 of 26 | Archive leaderboard | report |
| Link Property Prediction | ogbl-ppa | **Neural Common Neighbor ** | Validation Hits@100 | 0.6021 ± 0.0037 | #7 of 26 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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