• DocumentCode
    693139
  • Title

    Multi-view clustering ensembles

  • Author

    Xijiong Xie ; Shiliang Sun

  • Author_Institution
    Dept. of Comput. Sci. & Technol., East China Normal Univ., Shanghai, China
  • Volume
    01
  • fYear
    2013
  • fDate
    14-17 July 2013
  • Firstpage
    51
  • Lastpage
    56
  • Abstract
    Multi-view clustering and clustering ensembles have become increasingly popular in recent years. Multi-view clustering employs the relationship between views to cluster data; clustering ensembles combine different component clusterings to a better final partition. In this paper, we proposed the multi-view clustering ensembles which extend clustering ensembles to multi-view clustering. Experimental results show good performances of multi-view spectral clustering ensembles and multi-view kernel k-means clustering ensembles on real datasets.
  • Keywords
    pattern clustering; component clusterings; data clustering; multiview clustering ensembles; multiview kernel k-means clustering ensembles; multiview spectral clustering ensembles; Abstracts; Ionosphere; clustering ensembles; kernel k-means clustering; multi-view clustering; spectral clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2013 International Conference on
  • Conference_Location
    Tianjin
  • Type

    conf

  • DOI
    10.1109/ICMLC.2013.6890443
  • Filename
    6890443