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| Analisis Rangkaian Temporal Berlapis× | Deteksi Komunitas Berlapis× | |
|---|---|---|
| Bidang | Analisis Rangkaian | Analisis Rangkaian |
| Keluarga | Machine learning | Machine learning |
| Tahun asal≠ | 2012–2014 | 2010–2014 |
| Pengasas≠ | Kivela, M. et al.; Holme, P. & Saramaki, J. | Mucha, P. J. et al.; Kivela, M. et al. |
| Jenis≠ | Network analysis framework | Community detection algorithm for multilayer networks |
| Sumber perintis | Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271. DOI ↗ | Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271. DOI ↗ |
| Alias | MTNA, temporal multilayer network analysis, time-varying multilayer network analysis, dynamic multilayer network analysis | multilayer clustering, multiplex community detection, cross-layer community detection, MCD |
| Berkaitan≠ | 4 | 5 |
| Ringkasan≠ | Multilayer temporal network analysis studies relational systems in which nodes interact through multiple distinct types of ties that all evolve over time. By modeling each relationship type as a separate layer and tracking how those layers change across time snapshots, the method reveals how cross-layer dynamics and temporal patterns jointly shape information flow, influence spread, and community structure. | Multilayer community detection identifies groups of nodes that are densely connected across multiple types of relationships simultaneously. By coupling layers of a network — such as friendship, advice, and collaboration ties — it finds communities that are coherent not just within one relation type but across all of them, revealing structure that single-layer analysis would miss. |
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