• DocumentCode
    2165402
  • Title

    Fuzzy clustering of web documents using equivalence relations and fuzzy hierarchical clustering

  • Author

    Kumar, Sudhakar ; Kathuria, Madhumita ; Gupta, Amit Kumar ; Rani, Meenu

  • Author_Institution
    Dept. of Comput. Sci. & Eng., YMCA Univ. of Sci. & Technol., Faridabad, India
  • fYear
    2012
  • fDate
    5-7 Sept. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The conventional clustering algorithms have difficulties in handling the challenges posed by the collection of natural data which is often vague and uncertain. Fuzzy clustering methods have the potential to manage such situations efficiently. Fuzzy clustering method is offered to construct clusters with uncertain boundaries and allows that one object belongs to one or more clusters with some membership degree. In this paper, an algorithm and experimental results are presented for fuzzy clustering of web documents using equivalence relations and fuzzy hierarchical clustering.
  • Keywords
    Internet; data mining; document handling; fuzzy logic; learning (artificial intelligence); pattern clustering; Web documents; Web mining; equivalence relations; fuzzy hierarchical clustering; uncertain boundaries; unsupervised learning; Algorithm design and analysis; Clustering algorithms; Clustering methods; Euclidean distance; Information retrieval; Web mining; Clustering; Document Clustering; Fuzzy Clustering; Information Retrieval; Search Engine; Web Mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering (CONSEG), 2012 CSI Sixth International Conference on
  • Conference_Location
    Indore
  • Print_ISBN
    978-1-4673-2174-7
  • Type

    conf

  • DOI
    10.1109/CONSEG.2012.6349496
  • Filename
    6349496