• DocumentCode
    2285658
  • Title

    The growing hierarchical self-organizing map

  • Author

    Dittenbach, Michael ; Merkl, Dieter ; Rauber, Andreas

  • Author_Institution
    Inst. fur Softwaretech., Tech. Univ. Wien, Austria
  • Volume
    6
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    15
  • Abstract
    We present the growing hierarchical self-organizing map. This dynamically growing neural network model evolves into a hierarchical structure according to the requirements of the input data during an unsupervised training process. We demonstrate the benefits of this novel neural network model by organizing a real-world document collection according to their similarities
  • Keywords
    full-text databases; self-organising feature maps; unsupervised learning; dynamically growing neural network model; growing hierarchical self-organizing map; hierarchical structure; real-world document collection; unsupervised training process; Adaptive systems; Artificial neural networks; Data mining; Data visualization; Neural networks; Self organizing feature maps;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
  • Conference_Location
    Como
  • ISSN
    1098-7576
  • Print_ISBN
    0-7695-0619-4
  • Type

    conf

  • DOI
    10.1109/IJCNN.2000.859366
  • Filename
    859366
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2285658