TY - CHAP
T1 - Emotion-Age-Gender-Nationality Based Intention Understanding Using Two-Layer Fuzzy Support Vector Regression
AU - Chen, Luefeng
AU - Wu, Min
AU - Pedrycz, Witold
AU - Hirota, Kaoru
N1 - Publisher Copyright:
© 2020, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - An intention understanding model based on two-layer fuzzy support vector regression (TLFSVR) is proposed in human-robot interaction, where Fuzzy C-Means clustering is used to classify the input data, and intention understanding is mainly obtained by emotion, with identification information such as age, gender, and nationality. It aims to realize the transparent communication by understanding customers’ order intentions at a bar, in such a way that the social relationship between bar staffs and customers becomes smooth.
AB - An intention understanding model based on two-layer fuzzy support vector regression (TLFSVR) is proposed in human-robot interaction, where Fuzzy C-Means clustering is used to classify the input data, and intention understanding is mainly obtained by emotion, with identification information such as age, gender, and nationality. It aims to realize the transparent communication by understanding customers’ order intentions at a bar, in such a way that the social relationship between bar staffs and customers becomes smooth.
UR - http://www.scopus.com/inward/record.url?scp=85096207038&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-61577-2_11
DO - 10.1007/978-3-030-61577-2_11
M3 - Chapter
AN - SCOPUS:85096207038
T3 - Studies in Computational Intelligence
SP - 183
EP - 214
BT - Studies in Computational Intelligence
PB - Springer Science and Business Media Deutschland GmbH
ER -