TY - JOUR
T1 - Formalization and visualization of kansei information based on fuzzy set approach
AU - Dong, Fangyan
AU - Hirota, Kaoru
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - Kansei or affective-computing related information is easy to express in terms of fuzzy sets. Three examples of Kansei information, e.g., emotion, atmosphere, and Kansei texture, are formalized by using fuzzy set concept on [−1,1]3 space. They are also visualized by using shape-brightness-size, shape-color-size, and contour-shape-gradation models, respectively. Their applications to agent to agent communication, multiagent communication, and online shopping are also introduced.
AB - Kansei or affective-computing related information is easy to express in terms of fuzzy sets. Three examples of Kansei information, e.g., emotion, atmosphere, and Kansei texture, are formalized by using fuzzy set concept on [−1,1]3 space. They are also visualized by using shape-brightness-size, shape-color-size, and contour-shape-gradation models, respectively. Their applications to agent to agent communication, multiagent communication, and online shopping are also introduced.
UR - http://www.scopus.com/inward/record.url?scp=84930193722&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-19683-1_10
DO - 10.1007/978-3-319-19683-1_10
M3 - Article
AN - SCOPUS:84930193722
SN - 1434-9922
VL - 326
SP - 169
EP - 181
JO - Studies in Fuzziness and Soft Computing
JF - Studies in Fuzziness and Soft Computing
ER -