• DocumentCode
    3530436
  • Title

    A new approach to improve the accuracy of online clustering algorithm based on scatter/gather model

  • Author

    Farsandaj, Kian ; Ding, Chen ; Sadeghian, Alireza

  • Author_Institution
    Dept. of Comput. Sci., Ryerson Univ., Toronto, ON, Canada
  • fYear
    2010
  • fDate
    12-14 July 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In cluster analysis process used in data mining which enables extracting interesting data patterns from datasets, accuracy and efficiency are the factors which play a pivotal role. Scatter/Gather is a cluster-based browsing model, and most of previous works on this model focused on efficiency of the clustering algorithm. In this paper we present an algorithm which could improve the accuracy of the online clustering algorithm while still maintain a reasonable level of efficiency. Our experiment proves that the new algorithm is more accurate than the original algorithm.
  • Keywords
    data mining; pattern clustering; cluster analysis process; cluster based browsing model; data mining; online clustering algorithm; scatter-gather model; Algorithm design and analysis; Clustering algorithms; Clustering methods; Computer science; Couplings; Data mining; Partitioning algorithms; Pattern analysis; Prototypes; Scattering; Accuracy; Algorithms; Clustering; Data Mining; Efficiency; Homogeneity; Performance; Rand Index; Scatter/Gather;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society (NAFIPS), 2010 Annual Meeting of the North American
  • Conference_Location
    Toronto, ON
  • Print_ISBN
    978-1-4244-7859-0
  • Electronic_ISBN
    978-1-4244-7857-6
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2010.5548181
  • Filename
    5548181