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文章基本信息

  • 标题:A Scheme to Design Community Detection Algorithms in Various Networks
  • 作者:Haoye Lu ; Haoye Lu ; Amiya Nayak
  • 期刊名称:Future Internet
  • 电子版ISSN:1999-5903
  • 出版年度:2019
  • 卷号:11
  • 期号:2
  • 页码:41
  • DOI:10.3390/fi11020041
  • 语种:English
  • 出版社:MDPI Publishing
  • 摘要:Network structures, consisting of nodes and edges, have applications in almost all subjects. A set of nodes is called a community if the nodes have strong interrelations. Industries (including cell phone carriers and online social media companies) need community structures to allocate network resources and provide proper and accurate services. However, most detection algorithms are derived independently, which is arduous and even unnecessary. Although recent research shows that a general detection method that serves all purposes does not exist, we believe that there is some general procedure of deriving detection algorithms. In this paper, we represent such a general scheme. We mainly focus on two types of networks: transmission networks and similarity networks. We reduce them to a unified graph model, based on which we propose a method to define and detect community structures. Finally, we also give a demonstration to show how our design scheme works.
  • 关键词:social network; network modelling; community detection; network clustering social network ; network modelling ; community detection ; network clustering
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