Title :
Extraction of relationship among Kansei words by expert system using rough set analysis
Author :
Okuhara, Koji ; Matsubara, Yukihiro ; Ueno, Nobuyuki
Author_Institution :
Dept. of Manage. & Inf. Sci., Hiroshima Prefectural Univ., Shobara, Japan
Abstract :
In this paper, we propose the extended technique from the usual rough set analysis by considering the dominance relations to the quantitative data, and propose the criterion to select the rule. Proposed expert system using rough set analysis applies a most likelihood to estimate mapping from attributes of product to Kansei word. Usual estimation of interval efficiency has been developed by linear regression, however, our system can estimate interval efficiency by nonlinear mapping. As the experimental result, we analyze about the influence to user´s psychology from the front design of a car and extraction of relationship among Kansei words by expert system using rough set analysis.
Keywords :
automobiles; expert systems; maximum likelihood estimation; psychology; regression analysis; rough set theory; Kansei word; expert system; linear regression; nonlinear mapping; rough set analysis; user psychology; Data analysis; Data mining; Expert systems; Information analysis; Information management; Linear regression; Neurons; Probability density function; Psychology; Symmetric matrices;
Conference_Titel :
Active Media Technology, 2005. (AMT 2005). Proceedings of the 2005 International Conference on
Print_ISBN :
0-7803-9035-0
DOI :
10.1109/AMT.2005.1505397
