Encyclopedia of Social Network Analysis and Mining

Living Edition
| Editors: Reda Alhajj, Jon Rokne

Scalable Graph Clustering and Its Applications

  • Hiroaki ShiokawaEmail author
  • Makoto Onizuka
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7163-9_110185-1




A group of densely interconnected nodes

Community Detection

A function of network analysis that identifies groups of densely connected nodes.


A set of nodes and edges connecting the nodes


A special role of node that bridges multiple clusters


A graph extended with semantics and interactions between nodes and edges, respectively


A special role of node that is not hub and does not belong to any clusters. In many cases outliers are regarded as noises


Division of nonoverlapping subsets


Graph is one of the fundamental data structures and we can easily find graphs in many applications and services. Graph cluster analysis is a key technique to understand structures, characteristics, and interrelationships graphs. The problem of the graph cluster analysis is to find clusters inside of which nodes are densely connected and sparsely connected inter clusters, and this problem...


Betweenness Centrality Community Detection Graph Cluster Graph Cluster Algorithm Dynamic Community Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.Center for Computational SciencesUniversity of TsukubaIbarakiJapan
  2. 2.Graduate School of Information Science and TechnologyOsaka UniversityOsakaJapan

Section editors and affiliations

  • Huan Liu
    • 1
  • Lei Tang
    • 2
  1. 1.Arizona State UniversityTempeUSA
  2. 2.Chief Data Scientist, Clari Inc.SunnyvaleUSA