• DocumentCode
    3630023
  • Title

    Comparison of Two Document Clustering Techniques which use Neural Networks

  • Author

    I. Mokris;L. Skovajsova

  • Author_Institution
    Slovak Academy of Sciences, Bratislava, Slovakia, mokris@valm.sk
  • fYear
    2008
  • Firstpage
    75
  • Lastpage
    78
  • Abstract
    This paper presents text document space dimension reduction in text document retrieval by two different neural networks and their comparison. First neural network is Hebbian-type neural network, and second neural network is autoassociative neural network which uses backpropagation learning rule. Both neural networks reduce document space to two dimensions so each document is represented as a point in the reduced document space. Moreover, the clusters are formed in reduced document space. Both neural networks give promising results.
  • Keywords
    "Neural networks","Matrix decomposition","Information retrieval","Principal component analysis","Eigenvalues and eigenfunctions","Singular value decomposition","Internet","Computer networks","Backpropagation","Functional analysis"
  • Publisher
    ieee
  • Conference_Titel
    Computational Cybernetics, 2008. ICCC 2008. IEEE International Conference on
  • Print_ISBN
    978-1-4244-2874-8
  • Type

    conf

  • DOI
    10.1109/ICCCYB.2008.4721382
  • Filename
    4721382