• DocumentCode
    459030
  • Title

    Detect community structure from the Enron Email Corpus Based on Link Mining

  • Author

    Qian, Rong ; Zhang, Wei ; Yang, Bingru

  • Author_Institution
    Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing
  • Volume
    2
  • fYear
    2006
  • fDate
    16-18 Oct. 2006
  • Firstpage
    850
  • Lastpage
    855
  • Abstract
    There have been considerable recent interest algorithms for finding communities in networks. This paper presents an algorithm based on link mining. The algorithm is very fast, since calculating the clustering coefficient can be done with local information only. With the algorithm, the community structure from the Enron email corpus is detected. And the visualization of the graph is showed
  • Keywords
    Internet; data mining; electronic mail; graph theory; Enron email corpus; detect community structure; graph visualization; link clustering coefficient; link mining; social networks; Clustering algorithms; Collaboration; Electronic mail; Inspection; Internet; Nearest neighbor searches; Productivity; Social network services; Visualization; Web pages; Enron email corpus; detect community structure; link mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    0-7695-2528-8
  • Type

    conf

  • DOI
    10.1109/ISDA.2006.253723
  • Filename
    4021775