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
Link To Document :
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