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משפחהMachine learningMachine learning
שנת המקור20102004
הוגה השיטהOpsahl, T.; Agneessens, F.; Skvoretz, J.Barrat, A.; Barthélemy, M.; Pastor-Satorras, R.; Vespignani, A.
סוגCentrality measure (network analysis)Centrality measure for weighted networks
מקור מכונןOpsahl, T., Agneessens, F. & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks, 32(3), 245–251. DOI ↗Barrat, A., Barthélemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences, 101(11), 3747–3752. DOI ↗
כינוייםweighted closeness, generalized closeness centrality, WCC, distance-weighted closenessnode strength, strength centrality, weighted node degree, WDC
קשורות66
תקצירWeighted closeness centrality extends the classic closeness measure to networks where edges carry numerical weights — such as frequency, strength, or cost — by incorporating those weights into shortest-path distances. Nodes that can reach others quickly along strong or efficient connections receive higher scores, making it a richer indicator of information-spreading potential than its binary counterpart.Weighted degree centrality — also called node strength — extends the classic degree centrality measure to networks whose edges carry numeric weights. Instead of simply counting a node's connections, it sums the weights of all edges incident to that node, capturing both the volume and the intensity of a node's ties in a single, interpretable score.
ScholarGateמערך נתונים
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  1. v1
  2. 2 מקורות
  3. PUBLISHED

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ScholarGateהשוואת שיטות: Weighted Closeness Centrality · Weighted Degree Centrality. אוחזר בתאריך 2026-06-20 מתוך https://scholargate.app/he/compare