Notice of retraction
Vol. 32, No. 8(2), S&M2292

ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials, Volume 32, Number 10(1) (2020)
Copyright(C) MYU K.K.
pp. 3235-3242
S&M2335 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2020.2862
Published: October 9, 2020

System for Recommending Facial Skincare Products [PDF]

Chih-Hsien Hsia, Ting-Yu Lin, Jhe-Li Lin, Heri Prasetyo, Shih-Lun Chen, and Hsien-Wei Tseng

(Received March 15, 2020; Accepted June 30, 2020)

Keywords: acne, skincare, care product recommendation system, support vector machine

Acne is a skin problem that plagues many young people and adults. Even if it is cured, it leaves acne spots or acne scars and many individuals must use skincare products or undertake medical treatment. However, the use of inappropriate skincare products can exacerbate skin conditions. We propose the use of multifeature processing and classification of skin quality and acne status by machine learning to make recommendations for facial skincare products. The results for 15 subjects show that the proposed system achieves a consumer satisfaction index of 80%.

Corresponding author: Hsien-Wei Tseng


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This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Chih-Hsien Hsia, Ting-Yu Lin, Jhe-Li Lin, Heri Prasetyo, Shih-Lun Chen, and Hsien-Wei Tseng, System for Recommending Facial Skincare Products, Sens. Mater., Vol. 32, No. 10, 2020, p. 3235-3242.



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