A case study on the recommendation services for customized fashion styles based on artificial intelligence [인공지능에 의한 개인 맞춤 패션 스타일 추천 서비스 사례 연구]
- 주제(키워드) Artificial intelligence , Case study , Customized design , Fashion style , Recommendation service
- 관리정보기술 faculty
- 등재 SCOPUS, KCI등재
- 발행기관 Korean Society of Clothing and Textiles
- 발행년도 2019
- URI http://www.dcollection.net/handler/ewha/000000172133
- 본문언어 한국어
- Published As https://dx.doi.org/10.5850/JKSCT.2019.43.3.349
초록/요약
This study analyzes the trends of recommendation services for customized fashion styles in relation to artificial intelligence. To achieve this goal, the study examined filtering technologies of collaborative, content based, and deep-learning as well as analyzed the characteristics of recommendation services in the users' purchasing process. The results of this study showed that the most universal recommendation technology is collaborative filtering. Collaborative filtering was shown to allow intuitive searching of similar fashion styles in the cognition of need stage, and appeared to be useful in comparing prices but not suitable for innovative customers who pursue early trends. Second, content based filtering was shown to utilize body shape as a key personal profile item in order to reduce the possibility of failure when selecting sizes online, which has limits to being able to wear the product beforehand. Third, fashion style recommendations applied with deep-learning intervene with all user processes of buying products online that was also confirmed to penetrate into the creative area of image tag services, virtual reality services, clothes wearing fit evaluation services, and individually customized design services. © 2019, The Korean Society of Clothing and Textiles.
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