Abstract
Websites and magazines are now becoming more useful for general people to cook a dish everyday. Sometimes, we have inconvenience for such information because the listed ingredients in the recipe can not be prepared. This paper proposes a recommendation method of alternative ingredients towards such situation. The recommendation is realized by considering co-occurrence of ingredients on recipe database and ingredient category stored in a cooking ontology. The subjective evaluation experiments showed 88% appropriateness for the alternative-ingredients recommended by our proposed method. Also, the recommended ingredients were used in a real cooking, the good tastes were confirmed through the workshop.
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Acknowledgements
Yamanishi’s work was supported in part by Artificial Intelligence Research Promotion Foundation. And, in this paper, we used recipe data provided by Cookpad and the National Institute of Informatics.
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Shino, N., Yamanishi, R., Fukumoto, J. (2018). “Co-occurrence Relation” and “Ingredient Category” Recommend Alternative-Ingredients. In: Matsuo, T., Mine, T., Hirokawa, S. (eds) New Trends in E-service and Smart Computing. Studies in Computational Intelligence, vol 742. Springer, Cham. https://doi.org/10.1007/978-3-319-70636-8_1
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DOI: https://doi.org/10.1007/978-3-319-70636-8_1
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