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논문검색

심층신경망 기반의 뷰티제품 추천시스템

원문정보

Deep Neural Network-Based Beauty Product Recommender

송희석

피인용수 : 0(자료제공 : 네이버학술정보)

초록

영어

Many researchers have been focused on designing beauty product recommendation system for a long time because of increased need of customers for personalized and customized recommendation in beauty product domain. In addition, as the application of the deep neural network technique becomes active recently, various collaborative filtering techniques based on the deep neural network have been introduced. In this context, this study proposes a deep neural network model suitable for beauty product recommendation by applying Neural Collaborative Filtering and Generalized Matrix Factorization (NCF + GMF) to beauty product recommendation. This study also provides an implementation of web API system to commercialize the proposed recommendation model. The overall performance of the NCF + GMF model was the best when the beauty product recommendation problem was defined as the estimation rating score problem and the binary classification problem. The NCF + GMF model showed also high performance in the top N recommendation.

목차

Abstract
1. 서론
2. 기존 뷰티제품 추천 연구
3. 뷰티 제품 추천시스템
4. 성능평가 방법
5. 실험결과
5.1 데이터셋
5.2 실험결과
6. 결론
References

저자정보

  • 송희석 Hee Seok Song. Professor, Department of Global IT Business in Hannam University

참고문헌

자료제공 : 네이버학술정보

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