Abstract
People are increasingly searching for recipes online when they cook. At “cookpad” [1], Japan’s most popular recipe site, users can search for and contribute recipes. But since such recipe sites often fail to provide detailed nutrition information, users have to determine balanced nutrition by themselves. Hence, our system, which recommends a menu-list based on nutritional balance and considers user feedback about its recommended menu-list. When users input what they actually have eaten, our system recommends meals based on the feedback information after considering the entire nutritional content. The experimental results suggest that our system can provide useful nutrition information. These results were validated by a nutritional expert.
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Nishikawa, C., Nagai, A., Ito, T.: An Implementation of a Menu-List Recommendation System Providing Feedback from User. JAWS (2012) (in Japanese)
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Nishikawa, C., Nagai, A., Ito, T., Maruyama, S. (2013). An Implementation of a Menu-List Recommendation System Providing Feedback from User. In: Ali, M., Bosse, T., Hindriks, K., Hoogendoorn, M., Jonker, C., Treur, J. (eds) Contemporary Challenges and Solutions in Applied Artificial Intelligence. Studies in Computational Intelligence, vol 489. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00651-2_8
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DOI: https://doi.org/10.1007/978-3-319-00651-2_8
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00650-5
Online ISBN: 978-3-319-00651-2
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