• DocumentCode
    539322
  • Title

    Mining email transaction logs to locate significant messages and users

  • Author

    Esichaikul, Vatcharaporn ; Guha, Sumanta ; Niyamosatha, Thanittha

  • Author_Institution
    Comput. Sci. & Inf. Manage. Program, Asian Inst. of Technol., Pathumthani, Thailand
  • fYear
    2010
  • fDate
    Nov. 30 2010-Dec. 2 2010
  • Firstpage
    368
  • Lastpage
    371
  • Abstract
    A simple and intuitive model to mine an email transactions log for significant messages and users is presented. No use is made of NLP or semantic analysis. The model is based only on scoring messages and users from a graph-theoretic analysis of the communication pattern represented in the transaction log. Practical experiments indicate the potential of the model.
  • Keywords
    data mining; electronic mail; graph theory; email transaction log mining; graph-theoretic analysis; message scoring; Analytical models; Communities; Data mining; Databases; Electronic mail; Organizations; Postal services; Data mining; email; log mining; scoring model; significant message; significant user; transactions digraph; transactions log;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Information Management and Service (IMS), 2010 6th International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4244-8599-4
  • Electronic_ISBN
    978-89-88678-32-9
  • Type

    conf

  • Filename
    5713476