Papers › StarGraph: Knowledge Representation Learning based on Incomplete Two-hop Subgraph
StarGraph: Knowledge Representation Learning based on Incomplete Two-hop Subgraph
Hongzhu Li, Xiangrui Gao, Linhui Feng, Yafeng Deng, Yuhui Yin
Conventional representation learning algorithms for knowledge graphs (KG) map each entity to a unique embedding vector, ignoring the rich information contained in the neighborhood. We propose a method named StarGraph, which gives a novel way to utilize the neighborhood information for large-scale knowledge graphs to obtain entity representations. An incomplete two-hop neighborhood subgraph for each target node is at first generated, then processed by a modified self-attention network to obtain the entity representation, which is used to replace the entity embedding in conventional methods. We achieved SOTA performance on ogbl-wikikg2 and got competitive results on fb15k-237. The experimental results proves that StarGraph is efficient in parameters, and the improvement made on ogbl-wikikg2 demonstrates its great effectiveness of representation learning on large-scale knowledge graphs. The code is now available at \url{https://github.com/hzli-ucas/StarGraph}.
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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-wikikg2 | StarGraph + TripleRE | Ext. data | No | #6 of 30 | Archive leaderboard | report |
| Link Property Prediction | ogbl-wikikg2 | StarGraph + TripleRE | Number of params | 86762146 | #6 of 30 | Archive leaderboard | report |
| Link Property Prediction | ogbl-wikikg2 | StarGraph + TripleRE | Test MRR | 0.7201 ± 0.0011 | #6 of 30 | Archive leaderboard | report |
| Link Property Prediction | ogbl-wikikg2 | StarGraph + TripleRE | Validation MRR | 0.7288 ± 0.0008 | #6 of 30 | 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.
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