Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Modeli i peshuar stokastik i blloqeve× | Modeli Bllokues Stokastik× | |
|---|---|---|
| Fusha | Analiza e rrjeteve | Analiza e rrjeteve |
| Familja≠ | Machine learning | Process / pipeline |
| Viti i origjinës≠ | 2014 | 1983 |
| Krijuesi≠ | Aicher, C.; Jacobs, A. Z.; Clauset, A. | — |
| Lloji≠ | Generative probabilistic model | Probabilistic generative graph model |
| Burimi themelues≠ | Aicher, C., Jacobs, A. Z., & Clauset, A. (2014). Learning latent block structure in weighted networks. Journal of Complex Networks, 3(2), 221–248. DOI ↗ | Holland, P.W., Laskey, K.B. & Leinhardt, S. (1983). Stochastic Blockmodels: First Steps. Social Networks, 5(2), 109-137. DOI ↗ |
| Emërtime të tjera | W-SBM, weighted SBM, weighted block model, weighted community detection via SBM | SBM, degree-corrected SBM, DCSBM, Stokastik Blok Modeli (SBM) |
| Të lidhura≠ | 6 | 7 |
| Përmbledhja≠ | The Weighted Stochastic Block Model (W-SBM) extends the classical stochastic block model to networks whose edges carry numerical weights. By positing that edge weights between node pairs arise from distributions that depend on the block memberships of those nodes, it simultaneously infers a partition of nodes into communities and a set of block-to-block weight parameters — recovering structure invisible to unweighted methods. | 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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