• DocumentCode
    2549970
  • Title

    A Concept Based Indexing Approach for Document Clustering

  • Author

    Barresi, Simona ; Nefti, Samia ; Rezgui, Yacine

  • Author_Institution
    Univ. of Salford, Salford
  • fYear
    2008
  • fDate
    4-7 Aug. 2008
  • Firstpage
    26
  • Lastpage
    33
  • Abstract
    The research presented in this paper focuses on the pre-processing stage of the clustering process, proposing a novel indexing technique which goes beyond the syntax of terms; trying to capture their unambiguous meaning from their context and to derive a set of concepts to be used to represent the documents. This approach overcomes some of the major drawbacks deriving from the use of bag of words and term frequency based indexing techniques. The proposed approach is evaluated by using unsupervised performance measures and by comparing the clustering results achieved against the ones obtained when using a traditional indexing method. The experimental results show that better clustering results are achieved through the use of the proposed indexing approach, which also led to a substantial reduction of the index term dimension.
  • Keywords
    classification; document handling; indexing; vocabulary; bag of words technique; concept based indexing approach; document clustering; term frequency based indexing technique; unsupervised classification method; Algorithm design and analysis; Clustering algorithms; Frequency; Indexing; Partitioning algorithms; Clustering; Concept Indexing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantic Computing, 2008 IEEE International Conference on
  • Conference_Location
    Santa Clara, CA
  • Print_ISBN
    978-0-7695-3279-0
  • Electronic_ISBN
    978-0-7695-3279-0
  • Type

    conf

  • DOI
    10.1109/ICSC.2008.75
  • Filename
    4597170