Effective Semisupervised Community Detection Using Negative Information

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  • Additional Information
    • Publication Information:
      Hindawi Limited, 2015.
    • Publication Date:
      2015
    • Collection:
      LCC:Engineering (General). Civil engineering (General)
      LCC:Mathematics
    • Abstract:
      The semisupervised community detection method, which can utilize prior information to guide the discovery process of community structure, has aroused considerable research interests in the past few years. Most of the former works assume that the exact labels of some nodes are known in advance and presented in the forms of individual labels and pairwise constraints. In this paper, we propose a novel type of prior information called negative information, which indicates whether a node does not belong to a specific community. Then the semisupervised community detection algorithm is presented based on negative information to efficiently make use of this type of information to assist the process of community detection. The proposed algorithm is evaluated on several artificial and real-world networks and shows high effectiveness in recovering communities.
    • File Description:
      electronic resource
    • ISSN:
      1024-123X
      1563-5147
    • Relation:
      https://doaj.org/toc/1024-123X; https://doaj.org/toc/1563-5147
    • Accession Number:
      10.1155/2015/109671
    • Rights:
      Journal Licence: CC BY
    • Accession Number:
      edsdoj.f65924712449188dfc01fc60367238
  • Citations
    • ABNT:
      DONG LIU et al. Effective Semisupervised Community Detection Using Negative Information. Mathematical Problems in Engineering, [s. l.], 2015. Disponível em: . Acesso em: 15 out. 2019.
    • AMA:
      Dong Liu, Dequan Duan, Shikai Sui, Guojie Song. Effective Semisupervised Community Detection Using Negative Information. Mathematical Problems in Engineering. 2015. doi:10.1155/2015/109671.
    • APA:
      Dong Liu, Dequan Duan, Shikai Sui, & Guojie Song. (2015). Effective Semisupervised Community Detection Using Negative Information. Mathematical Problems in Engineering. https://doi.org/10.1155/2015/109671
    • Chicago/Turabian: Author-Date:
      Dong Liu, Dequan Duan, Shikai Sui, and Guojie Song. 2015. “Effective Semisupervised Community Detection Using Negative Information.” Mathematical Problems in Engineering. doi:10.1155/2015/109671.
    • Harvard:
      Dong Liu et al. (2015) ‘Effective Semisupervised Community Detection Using Negative Information’, Mathematical Problems in Engineering. doi: 10.1155/2015/109671.
    • Harvard: Australian:
      Dong Liu, Dequan Duan, Shikai Sui & Guojie Song 2015, ‘Effective Semisupervised Community Detection Using Negative Information’, Mathematical Problems in Engineering, viewed 15 October 2019, .
    • MLA:
      Dong Liu, et al. “Effective Semisupervised Community Detection Using Negative Information.” Mathematical Problems in Engineering, 2015. EBSCOhost, doi:10.1155/2015/109671.
    • Chicago/Turabian: Humanities:
      Dong Liu, Dequan Duan, Shikai Sui, and Guojie Song. “Effective Semisupervised Community Detection Using Negative Information.” Mathematical Problems in Engineering, 2015. doi:10.1155/2015/109671.
    • Vancouver/ICMJE:
      Dong Liu, Dequan Duan, Shikai Sui, Guojie Song. Effective Semisupervised Community Detection Using Negative Information. Mathematical Problems in Engineering [Internet]. 2015 [cited 2019 Oct 15]; Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsdoj&AN=edsdoj.f65924712449188dfc01fc60367238&custid=s8280428