方法证据记录
Weighted Community Detection
Weighted community detection identifies densely connected groups — communities — in networks where edges carry numeric strengths (weights). By incorporating edge weights into the modularity function, it reveals structure that binary adjacency alone would miss: two nodes connected by a strong tie are treated as more similar than two nodes linked by a weak one. The Louvain algorithm is the dominant practical implementation.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Weighted Community Detection in Networks
分类方法记录 · ml-model / network-analysis
- Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008. · DOI 10.1088/1742-5468/2008/10/P10008
- Newman, M. E. J. (2004). Analysis of weighted networks. Physical Review E, 70(5), 056131. · DOI 10.1103/PhysRevE.70.056131
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