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개인 맞춤형 음식 추천 알고리즘에 대한 비교 평가 연구
정영윤,박민규,김건우,김석환,박경신 한국정보통신학회 2023 한국정보통신학회논문지 Vol.27 No.3
A recommendation system is a method of recommending content that may be interest to users, and it has been actively studied in various fields such as e-commere products, movies, music and news. With the increased in non-face-to-face services, the recommendation system customized to consumer’s tastes and lifestyles is becoming more important. However, in the field of food, the food classification criteria are relatively ambiguous and the taste cannot be defined objectively, making it difficult to calculate the similarity based on the content. Also, the concept of food evaluation is unfamiliar, so the cold start problem was not avoided in collaborative filtering based recommendation system. Therefore, in this study, we propose algorithms that additionally utilize main ingredients, food descriptions, and recipes that can represent food characteristics in the most widely used user-based collaborative filtering, and discuss comparative evaluation of these algorithms.