• DocumentCode
    2133258
  • Title

    Hierarchical clustering of free form questionnaires using domain knowledge

  • Author

    Moriya, Kunihiko ; Shioya, Isarnu ; Miura, Tsuyoshi ; Miyauchi, Minami

  • Author_Institution
    Sanno Univ., Kanagawa, Japan
  • Volume
    2
  • fYear
    2003
  • fDate
    28-30 Aug. 2003
  • Firstpage
    812
  • Abstract
    In this paper, we propose a new statistical analysis method of free form questionnaires for discovering unexpected themes by artificial intelligence technique. Then, we use hierarchical clustering method through similarity measure based on domain knowledge. We applied our method to an actual data of a free form questionnaire to university students, and we obtained that the semantic average metrics between every pairs of two words within the same clusters are condensed more than conventional one without domain knowledge.
  • Keywords
    artificial intelligence; pattern clustering; statistical analysis; artificial intelligence technique; free form questionnaire; hierarchical clustering; semantic average metric; statistical analysis method; unexpected theme discovering; Artificial intelligence; Clustering methods; Data mining; Decision making; Educational institutions; Length measurement; Marketing and sales; Product development; Statistical analysis; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Computers and signal Processing, 2003. PACRIM. 2003 IEEE Pacific Rim Conference on
  • Print_ISBN
    0-7803-7978-0
  • Type

    conf

  • DOI
    10.1109/PACRIM.2003.1235905
  • Filename
    1235905