• DocumentCode
    3698100
  • Title

    Interval Type-2 fuzzy C-Means approach to collaborative clustering

  • Author

    Trong Hop Dang; Long Thanh Ngo;Witold Pedrycz

  • Author_Institution
    Department of Information Systems, Le Quy Don Technical University, 236 Hoang Quoc Viet, Hanoi, Vietnam
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    There have been numerous studies on using the FCM algorithm in clustering and collaboration clustering, especially in data analysis, data mining and pattern recognition. In this study, we present new methods involving interval Type-2 fuzzy sets to realize collaborative clustering. Data in which the clustering results realized at one data site impact clustering carried out at other data sites. Those methods endowed with interval type-2 fuzzy sets help cope with uncertainties present in data. The experiment with weather data sets has shown better results in comparison with the previous approaches.
  • Keywords
    "Collaboration","Fuzzy sets","Clustering algorithms","Uncertainty","Linear programming","Prototypes","Pattern recognition"
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2015.7337932
  • Filename
    7337932