A cognitive knowledge-based system for hair and makeup recommendation based on facial features classification
Juhyun Lee, Joosun Yum, Marvin Lee, Ji–Hyun Lee · 2022
This paper aims at building a knowledge-based system of smart mirrors for the cosmetic industry. In order to better understand hair and cosmetic experts, we first conduct interviews for knowledge acquisition. Then, we obtain insights from each category of answers collected from expert interviews. To design this knowledge-based system, we define concepts, main tasks and subtasks in order to extract rules to design the system. This system can suggest hairstyles and make-up colors by considering users’ face shapes and their personal colors.