• DocumentCode
    3424212
  • Title

    Clustering based-on indiscernibility and indiscernibility level

  • Author

    Hakim, R.B.F. ; Winarko, Edi

  • Author_Institution
    Stat. Dept., Universitas Islam Indonesia, Sleman, Indonesia
  • fYear
    2009
  • fDate
    17-19 Aug. 2009
  • Firstpage
    192
  • Lastpage
    196
  • Abstract
    The core concept of classical rough sets are clustering similarities and dissimilarities of objects based on the notions of indiscernibility and discernibility. In this paper, we present a new method of clustering data based on the combination of indiscernibility and its indiscernibility level. The indiscernibility level quantifies the indiscernibility of pairs of objects among other objects in information systems. The result of this paper show the dual notions of indiscernibility and its indiscernibility level play an important role in clustering information systems.
  • Keywords
    information systems; pattern clustering; data clustering; indiscernibility level; information system clustering; Clustering algorithms; Clustering methods; Customer relationship management; Data analysis; Information systems; Management information systems; Mathematics; Rough sets; Set theory; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing, 2009, GRC '09. IEEE International Conference on
  • Conference_Location
    Nanchang
  • Print_ISBN
    978-1-4244-4830-2
  • Type

    conf

  • DOI
    10.1109/GRC.2009.5255132
  • Filename
    5255132