• DocumentCode
    2219326
  • Title

    An Incremental Clustering Algorithm Based on Subcluster Feature

  • Author

    Meng, Hai-Dong ; Song, Yu-Chen ; Wang, Shu-Ling

  • Author_Institution
    Inner Mongolia Univ. of Sci. & Technol., Baotou, China
  • fYear
    2009
  • fDate
    26-28 Dec. 2009
  • Firstpage
    786
  • Lastpage
    789
  • Abstract
    For very large databases, such as spatial database and multimedia database, the traditional clustering algorithms are of limitations in validity and scalability. According to the notion of clustering feature of BIRCH, an incremental clustering algorithm is designed and implemented, which solves the problems of effectiveness, space and time complexities of clustering algorithms for very large spatial databases. Theoretic analysis and experimental results demonstrate that the incremental clustering algorithm cannot only handle very large spatial databases, but also has good performance.
  • Keywords
    multimedia databases; pattern clustering; very large databases; visual databases; BIRCH; incremental clustering algorithm; multimedia database; space complexities; spatial database; subcluster feature; time complexities; very large databases; Algorithm design and analysis; Clustering algorithms; Image databases; Multimedia databases; Partitioning algorithms; Performance analysis; Sampling methods; Shape; Space technology; Spatial databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2009 1st International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4909-5
  • Type

    conf

  • DOI
    10.1109/ICISE.2009.282
  • Filename
    5455002