Journal of University of Science and Technology of China ›› 2014, Vol. 44 ›› Issue (7): 563-569.DOI: 10.3969/j.issn.0253-2778.2014.07.004

• Original Paper • Previous Articles     Next Articles

Community detection based on structure and fitness

GAO Qihang, JING Liping, YU Jian, LIN Youfang   

  1. Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China
  • Received:2014-03-21 Revised:2014-06-15 Accepted:2014-06-15 Online:2023-05-11 Published:2014-06-15

Abstract: Many systems can be described as complex social networks, and increasing attention has been paid to the detection of social communities out of complex social networks. Structured-based community detection can be achieved locally without knowledge of the overall situation. The community fitness characteristics of social networks can help to identify community structures at different fitnesses. A new algorithm based on structure and fitness was proposed to test large generated networks and real networks. Experiments had shown its better efficiency and higher accuracy.

Key words: community detection, community structure, community fitness, large networks, local community

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