A recipe recommendation system that considers user's mood
Mayumi Ueda, Yukitoshi Morishita, Tomiyo Nakamura, Natsuhiko Takata, Shinsuke Nakajima · 2016
Homemaker decide what to cook based on the mood they are in, the ingredients they have in their refrigerators, or the ingredients offered in a supermarket. Most of the existing services for searching recipes allow ingredient names or recipe names as search input. We propose a system that allows searching recipes based on the users' mood. To develop the system, we gather words to express a user's mood when making a menu decision and classify them according to their relationship. We determine six aspects of a user's mood. The result of our preliminary experiment and a questionnaire-based survey show that our method describes a user's mood when deciding for a menu and that the system helps in the decision-making. Furthermore, we propose a method for automatically generating recipe metadata, which we plan to add to our system.