• DocumentCode
    2743476
  • Title

    Clustering ICT Indicators of Bhutan using Two Level HSOM Algorithm

  • Author

    Tshering ; Arch-int, Somjit

  • Author_Institution
    Khon Kaen Univ., Khon Kaen
  • fYear
    2008
  • fDate
    6-8 Aug. 2008
  • Firstpage
    121
  • Lastpage
    127
  • Abstract
    In this paper, a novel two level HSOM algorithm for clustering information and communication technology (ICT) indicators is presented. The purpose of this research study is to analyze the twenty districts ICT data of Bhutan using HSOM clustering algorithm. The HSOM possesses a two-level hybrid connectionist architecture that comprises (i) an agglomerative hierarchical clustering algorithm to create hierarchy of data in dendrogram from the principal component analysis(PCA) reduced data and (ii) an unsupervised neural network based Self-Organizing map classifier,which generates the final cluster output in single umatrix map. It is confirmed that HSOM obtains the effective output reflecting distribution state of input data. Ultimately we analyzed present scenario of ICT situation with clustering algorithm. ICT is one of the enabler of socio-economic developmental activities in Bhutan. Outcome from this research will help newly elected democratic government to achieve sustain able and equitable development in its 10th five year plan (2008-2013).
  • Keywords
    government; information technology; pattern clustering; principal component analysis; self-organising feature maps; socio-economic effects; unsupervised learning; HSOM algorithm; HSOM clustering algorithm; agglomerative hierarchical clustering algorithm; clustering ICT indicators; clustering information and communication technology indicators; democratic government; principal component analysis; self-organizing map classifier; socio-economic developmental activity; two-level hybrid connectionist architecture; umatrix map; unsupervised neural network; Algorithm design and analysis; Artificial intelligence; Clustering algorithms; Data analysis; Hybrid power systems; Neural networks; Principal component analysis; Software algorithms; Software engineering; Statistical analysis; Clustering; HSOM; PCA; SOM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2008. SNPD '08. Ninth ACIS International Conference on
  • Conference_Location
    Phuket
  • Print_ISBN
    978-0-7695-3263-9
  • Type

    conf

  • DOI
    10.1109/SNPD.2008.22
  • Filename
    4617359