• DocumentCode
    2129198
  • Title

    Research on incremental clustering

  • Author

    Liu, Yongli ; Guo, Qianqian ; Yang, Lishen ; Li, Yingying

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Henan Polytech. Univ., Jiaozuo, China
  • fYear
    2012
  • fDate
    21-23 April 2012
  • Firstpage
    2803
  • Lastpage
    2806
  • Abstract
    Currently, incremental document clustering is one the most effective techniques to organize documents in an unsupervised manner for many Web applications. This paper summarizes the research actuality and new progress in incremental clustering algorithm in recent years. First, some representative algorithms are analyzed and generalized from such aspects as algorithm thinking, key technique, advantage and disadvantage. Secondly, we select four typical clustering algorithms and carry out simulation experiments to compare their clustering quality from both accuracy and efficiency. The work in this paper can give a valuable reference for incremental clustering research.
  • Keywords
    Internet; data mining; document handling; pattern clustering; Web applications; algorithm thinking; clustering quality; documents organization; incremental document clustering; key technique; representative algorithms; simulation experiments; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Clustering methods; Databases; Entropy; Internet; Web mining; algorithms; experiments; incremental clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics, Communications and Networks (CECNet), 2012 2nd International Conference on
  • Conference_Location
    Yichang
  • Print_ISBN
    978-1-4577-1414-6
  • Type

    conf

  • DOI
    10.1109/CECNet.2012.6202079
  • Filename
    6202079