Papers › struc2vec: Learning Node Representations from Structural Identity
struc2vec: Learning Node Representations from Structural Identity
Leonardo F. R. Ribeiro, Pedro H. P. Saverese, Daniel R. Figueiredo
Implementation and experiments of graph embedding algorithms.deep walk,LINE(Large-scale Information Network Embedding),node2vec,SDNE(Structural Deep Network Embedding),struc2vec
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3 samples harvested; 3 ran; 1 honoured the contract we drafted; 0 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.
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Tasks
Datasets
Introduced by this paper, per the archive.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Node Classification | Eximtradedata | Struc2vec | Accuracy | 22.80% | #1 of 5 | Archive leaderboard | report |
| Node Classification | Eximtradedata | Struc2vec | Macro-F1 | 0.216 | #1 of 5 | Archive leaderboard | report |
| Node Classification | Wikipedia | Struc2vec | Accuracy | 21.10% | #2 of 6 | Archive leaderboard | report |
| Node Classification | Wikipedia | Struc2vec | Macro-F1 | 0.190 | #2 of 6 | 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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