• DocumentCode
    2924352
  • Title

    Soft clustering from crisp clustering using granulation for mobile call mining

  • Author

    Lingras, P. ; Nimse, S. ; Darkunde, N. ; Muley, A.

  • Author_Institution
    Dept. of Math. & Comput. Sci., St. Mary´´s Univ., Halifax, NS, Canada
  • fYear
    2011
  • fDate
    8-10 Nov. 2011
  • Firstpage
    410
  • Lastpage
    416
  • Abstract
    This paper builds on an earlier study for transforming clustering schemes between two levels of granularity. A crisp clustering scheme of coarse granules can be easily transferred to a crisp clustering at finer level of granularity. However, crisp clustering of finer granules cannot be easily transferred to coarser granules due to the non-overlapping nature of crisp clusters. We propose the use of soft clustering schemes, which allow for possible overlap of clusters. The clustering of finer granules given by phone calls is first transferred to fuzzy clustering and then to rough clustering. The process highlights the complementary nature of fuzzy and rough set theory.
  • Keywords
    data mining; fuzzy set theory; pattern clustering; rough set theory; coarse granules; crisp clustering scheme; fuzzy clustering; fuzzy set theory; mobile call mining granulation; nonoverlapping nature; phone calls; rough clustering; rough set theory; soft clustering; Clustering algorithms; Data mining; Mobile communication; Mobile computing; Mobile handsets; Social network services; Upper bound; Clustering; fuzzy clustering; granular computing; k-means; mobile call mining; rough clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Granular Computing (GrC), 2011 IEEE International Conference on
  • Conference_Location
    Kaohsiung
  • Print_ISBN
    978-1-4577-0372-0
  • Type

    conf

  • DOI
    10.1109/GRC.2011.6122632
  • Filename
    6122632