• DocumentCode
    1844847
  • Title

    An Extended Grid-based Clustering Algorithm with Referential Value of Parameters

  • Author

    Zhou, Yantao ; Wu, Zhengguo ; Yi, Xingdong

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha
  • fYear
    2008
  • fDate
    18-21 Nov. 2008
  • Firstpage
    1832
  • Lastpage
    1837
  • Abstract
    GRPC algorithm (a grid-based clustering algorithm with referential parameters) had put forward by authors of this paper, and the algorithm provided user with a feasible technology for reducing the blindness of parameter assignment. The work of this paper is to develop GRPC algorithm in the aspects of scalability and high-dimensionality. We process large-scale data set by means of random sampling technique and transform the clustering of high-dimensional data into the clustering of two-dimensional data. Experimental results confirmed that this algorithm (EGRPC) could effectively cluster vast data set whose data is three-dimensional or other high-dimensional.
  • Keywords
    grid computing; pattern clustering; random processes; extended grid-based clustering algorithm; random sampling technique; referential parameters; Algorithm design and analysis; Clustering algorithms; Gravity; Grid computing; Large-scale systems; Paper technology; Partitioning algorithms; Sampling methods; Scalability; Shape; Clustering; Grid; density threshold; high dimension; referential parameter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
  • Conference_Location
    Hunan
  • Print_ISBN
    978-0-7695-3398-8
  • Electronic_ISBN
    978-0-7695-3398-8
  • Type

    conf

  • DOI
    10.1109/ICYCS.2008.162
  • Filename
    4709252