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Memorias de investigación
Artículos en revistas:
A network reduction-based multiobjective evolutionary algorithm for community detection in large-scale complex networks
Año:2018
Áreas de investigación
  • Inteligencia artificial
Datos
Descripción
Evolutionary algorithms have been demonstrated to be very competitive in the community detection for complex networks. They, however, show poor scalability to large-scale networks due to the exponential increase of search space. In this paper, we suggest a network reduction-based multiobjective evolutionary algorithm for community detection in large-scale networks, where the size of the networks is recursively reduced as the evolution proceeds. In each reduction of the network, the local communities found by the elite individuals in the population are identified as nodes of the reduced network for further evolution, thereby considerably reducing the search space. A local community repairing strategy is also suggested to correct the misidentified nodes after each network reduction during the evolution. Experimental results on synthetic and real-world networks demonstrate the superiority of the proposed ?
Internacional
Si
JCR del ISI
Si
Título de la revista
Ieee Transactions on Cybernetics
ISSN
2168-2267
Factor de impacto JCR
8,803
Información de impacto
Volumen
DOI
Número de revista
Desde la página
1
Hasta la página
14
Mes
SIN MES
Ranking
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Xingyi Zhang
  • Autor: Kefei Zhou
  • Autor: Hebin Pan
  • Autor: Lei Zhang
  • Autor: Xiangxiang Zeng . (UPM)
  • Autor: Yaochu Jin
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Inteligencia Artificial (LIA)
  • Departamento: Inteligencia Artificial
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