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Linganisha mbinu

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Uchambuzi wa Modularityi yenye Uzito×Ukalimani Kati×
NyanjaUchanganuzi wa MitandaoUchanganuzi wa Mitandao
FamiliaMachine learningMachine learning
Mwaka wa asili20041977
MwanzilishiNewman, M. E. J.Freeman, L. C.
AinaCommunity structure optimization on weighted graphsCentrality measure
Chanzo asiliaNewman, M. E. J. (2004). Analysis of weighted networks. Physical Review E, 70(5), 056131. DOI ↗Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41. DOI ↗
Majina mbadalaweighted modularity, weighted Q optimization, weighted network community detection, strength-based modularityFreeman betweenness, BC, geodesic betweenness, shortest-path betweenness
Zinazohusiana56
MuhtasariWeighted modularity analysis extends the classical Newman-Girvan modularity measure to networks where edges carry numeric strengths (frequencies, intensities, costs). By replacing binary adjacency with tie weights, it finds community partitions that reflect how densely interconnected subgroups are relative to what is expected under a weighted null model, yielding more nuanced groupings than unweighted approaches on data where edge strength varies meaningfully.Betweenness centrality, formalized by Linton C. Freeman in 1977, measures how often a node lies on the shortest path connecting every other pair of nodes in a network. High-betweenness nodes act as bridges or brokers: removing them fragments the network into disconnected components more severely than removing any other nodes.
ScholarGateSeti ya data
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  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: Weighted Modularity Analysis · Betweenness Centrality. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare