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משפחהMachine learningMachine learning
שנת המקור2013–20141950 (formalized 1979)
הוגה השיטהKivela, M. et al.; De Domenico, M. et al.Bavelas, A.; formalized by Freeman, L. C.
סוגCentrality measure for multilayer networksNode-level centrality index
מקור מכונןKivela, 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 ↗Freeman, L. C. (1979). Centrality in social networks: Conceptual clarification. Social Networks, 1(3), 215–239. DOI ↗
כינוייםmultilayer closeness, multi-layer closeness centrality, MLC, interlayer closeness centralitycloseness, farness-based centrality, geodesic closeness, normalized closeness centrality
קשורות56
תקצירMultilayer closeness centrality extends the classical closeness centrality measure to networks that contain multiple types of relationships or interaction contexts (layers). Rather than treating each layer in isolation, it computes how quickly a node can reach all others by traversing any combination of available layers, revealing nodes that are structurally efficient connectors across the full network system.Closeness centrality measures how quickly a node can reach all others in a network by computing the inverse of its average shortest-path distance to every other node. First described by Bavelas (1950) and formally unified by Freeman (1979), it identifies nodes that can spread information or resources efficiently across the entire graph — not merely nodes with many direct contacts.
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ScholarGateהשוואת שיטות: Multilayer Closeness Centrality · Closeness Centrality. אוחזר בתאריך 2026-06-19 מתוך https://scholargate.app/he/compare