Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| Link Prediction× | Stochastic Block Model× | |
|---|---|---|
| Valdkond | Võrgustikuanalüüs | Võrgustikuanalüüs |
| Perekond | Process / pipeline | Process / pipeline |
| Tekkeaasta≠ | 2003 | 1983 |
| Looja | — | — |
| Tüüp≠ | Network inference task | Probabilistic generative graph model |
| Algallikas≠ | Liben-Nowell, D. & Kleinberg, J. (2007). The Link-Prediction Problem for Social Networks. Journal of the American Society for Information Science and Technology, 58(7), 1019-1031. DOI ↗ | Holland, P.W., Laskey, K.B. & Leinhardt, S. (1983). Stochastic Blockmodels: First Steps. Social Networks, 5(2), 109-137. DOI ↗ |
| Rööpnimetused | Bağlantı Tahmini (Link Prediction), missing link prediction, future link prediction, edge prediction | SBM, degree-corrected SBM, DCSBM, Stokastik Blok Modeli (SBM) |
| Seotud≠ | 5 | 7 |
| Kokkuvõte≠ | Link prediction is a network-analysis task that estimates which edges are missing from an observed graph or which edges are likely to form in the future. Formalised by Liben-Nowell and Kleinberg (2003, 2007), it covers a spectrum of approaches — from simple structural similarity indices such as Common Neighbors, Jaccard coefficient, and Adamic-Adar, to matrix factorisation, and graph neural network (GNN) methods — and is evaluated with AUC and Average Precision to account for the heavily imbalanced ratio of real to non-existing edges. | The Stochastic Block Model (SBM), introduced by Holland, Laskey and Leinhardt (1983), is a probabilistic generative model for graphs that assigns nodes to latent blocks and parametrically estimates the connection probabilities between blocks. It is the foundational approach for community detection, core-periphery identification, and hierarchical structure discovery in network analysis. |
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