ScholarGate
アシスタント

手法を比較

選択した手法を並べて確認できます。異なる行はハイライト表示されます。

動的コミュニティ検出×多層コミュニティ検出×
分野ネットワーク分析ネットワーク分析
系統Machine learningMachine learning
提唱年2010 (key formalization); earlier work 2002–20092010–2014
提唱者Mucha, P. J. et al. (key formalization); earlier work by Girvan & Newman (2002)Mucha, P. J. et al.; Kivela, M. et al.
種類Graph clustering / community discoveryCommunity detection algorithm for multilayer networks
原典Mucha, P. J., Richardson, T., Macon, K., Porter, M. A., & Onnela, J.-P. (2010). Community structure in time-dependent, multiscale, and multiplex networks. Science, 328(5980), 876–878. 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 ↗
別名DCD, temporal community detection, evolving community detection, dynamic graph clusteringmultilayer clustering, multiplex community detection, cross-layer community detection, MCD
関連55
概要Dynamic community detection identifies groups of densely connected nodes in networks that evolve over time, tracking how communities form, merge, split, and dissolve across temporal snapshots. Developed to extend static modularity optimization to time-varying structures, it is widely used in social, biological, and communication network research.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.
ScholarGateデータセット
  1. v1
  2. 2 出典
  3. PUBLISHED
  1. v1
  2. 2 出典
  3. PUBLISHED

検索へ スライドをダウンロード

ScholarGate手法を比較: Dynamic Community Detection · Multilayer Community Detection. 2026-06-18に以下より取得 https://scholargate.app/ja/compare