Papers › SEEK: Segmented Embedding of Knowledge Graphs
SEEK: Segmented Embedding of Knowledge Graphs
Wentao Xu, Shun Zheng, Liang He, Bin Shao, Jian Yin, Tie-Yan Liu
In recent years, knowledge graph embedding becomes a pretty hot research topic of artificial intelligence and plays increasingly vital roles in various downstream applications, such as recommendation and question answering. However, existing methods for knowledge graph embedding can not make a proper trade-off between the model complexity and the model expressiveness, which makes them still far from satisfactory. To mitigate this problem, we propose a lightweight modeling framework that can achieve highly competitive relational expressiveness without increasing the model complexity. Our framework focuses on the design of scoring functions and highlights two critical characteristics: 1) facilitating sufficient feature interactions; 2) preserving both symmetry and antisymmetry properties of relations. It is noteworthy that owing to the general and elegant design of scoring functions, our framework can incorporate many famous existing methods as special cases. Moreover, extensive experiments on public benchmarks demonstrate the efficiency and effectiveness of our framework. Source codes and data can be found at \url{https://github.com/Wentao-Xu/SEEK}.
In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Link Prediction | FB15k | SEEK | Hits@1 | 0.792 | #4 of 23 | Archive leaderboard | report |
| Link Prediction | FB15k | SEEK | Hits@10 | 0.886 | #4 of 23 | Archive leaderboard | report |
| Link Prediction | FB15k | SEEK | Hits@3 | 0.841 | #4 of 23 | Archive leaderboard | report |
| Link Prediction | FB15k | SEEK | MRR | 0.825 | #4 of 23 | Archive leaderboard | report |
| Link Prediction | YAGO37 | SEEK | Hits@1 | 0.370 | #1 of 2 | Archive leaderboard | report |
| Link Prediction | YAGO37 | SEEK | Hits@10 | 0.622 | #1 of 2 | Archive leaderboard | report |
| Link Prediction | YAGO37 | SEEK | Hits@3 | 0.498 | #1 of 2 | Archive leaderboard | report |
| Link Prediction | YAGO37 | SEEK | MRR | 0.454 | #1 of 2 | 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.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections