Emotion-Age-Gender-Nationality Based Intention Understanding Using Two-Layer Fuzzy Support Vector Regression

Luefeng Chen; Min Wu; Witold Pedrycz; Kaoru Hirota

doi:10.1007/978-3-030-61577-2_11

Emotion-Age-Gender-Nationality Based Intention Understanding Using Two-Layer Fuzzy Support Vector Regression

Luefeng Chen^*, Min Wu, Witold Pedrycz, Kaoru Hirota

^*此作品的通讯作者

科研成果: 书/报告/会议事项章节 › 章节 › 同行评审

摘要

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.

源语言	英语
主期刊名	Studies in Computational Intelligence
出版商	Springer Science and Business Media Deutschland GmbH
页	183-214
页数	32
DOI	https://doi.org/10.1007/978-3-030-61577-2_11
出版状态	已出版 - 2021
已对外发布	是

出版系列

姓名	Studies in Computational Intelligence
卷	926
ISSN（印刷版）	1860-949X
ISSN（电子版）	1860-9503

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10.1007/978-3-030-61577-2_11

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引用此

Chen, L., Wu, M., Pedrycz, W., & Hirota, K. (2021). Emotion-Age-Gender-Nationality Based Intention Understanding Using Two-Layer Fuzzy Support Vector Regression. 在 Studies in Computational Intelligence (页码 183-214). (Studies in Computational Intelligence; 卷 926). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-61577-2_11

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abstract = "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{\textquoteright} order intentions at a bar, in such a way that the social relationship between bar staffs and customers becomes smooth.",

author = "Luefeng Chen and Min Wu and Witold Pedrycz and Kaoru Hirota",

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Emotion-Age-Gender-Nationality Based Intention Understanding Using Two-Layer Fuzzy Support Vector Regression. / Chen, Luefeng; Wu, Min; Pedrycz, Witold 等.
Studies in Computational Intelligence. Springer Science and Business Media Deutschland GmbH, 2021. 页码 183-214 (Studies in Computational Intelligence; 卷 926).

科研成果: 书/报告/会议事项章节 › 章节 › 同行评审

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T1 - Emotion-Age-Gender-Nationality Based Intention Understanding Using Two-Layer Fuzzy Support Vector Regression

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AU - Pedrycz, Witold

AU - Hirota, Kaoru

PY - 2021

Y1 - 2021

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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.

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PB - Springer Science and Business Media Deutschland GmbH

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Emotion-Age-Gender-Nationality Based Intention Understanding Using Two-Layer Fuzzy Support Vector Regression

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