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dc.contributor.authorMorales Garzón, Andrea
dc.contributor.authorGómez Romero, Juan 
dc.contributor.authorMartín Bautista, María José 
dc.date.accessioned2021-03-10T12:52:21Z
dc.date.available2021-03-10T12:52:21Z
dc.date.issued2021
dc.identifier.citationA. Morales-Garzón, J. Gómez-Romero and M. J. Martin-Bautista, "A Word Embedding-Based Method for Unsupervised Adaptation of Cooking Recipes," in IEEE Access, vol. 9, pp. 27389-27404, 2021, doi: 10.1109/ACCESS.2021.3058559.es_ES
dc.identifier.urihttp://hdl.handle.net/10481/67064
dc.description.abstractStudying food recipes is indispensable to understand the science of cooking. An essential problem in food computing is the adaptation of recipes to user needs and preferences. The main difficulty when adapting recipes is in determining ingredients relations, which are compound and hard to interpret. Word embedding models can catch the semantics of food items in a recipe, helping to understand how ingredients are combined and substituted. In this work, we propose an unsupervised method for adapting ingredient recipes to user preferences. To learn food representations and relations, we create and apply a specific-domain word embedding model. In contrast to previous works, we not only use the list of ingredients to train the model but also the cooking instructions. We enrich the ingredient data by mapping them to a nutrition database to guide the adaptation and find ingredient substitutes. We performed three different kinds of recipe adaptation based on nutrition preferences, adapting to similar ingredients, and vegetarian and vegan diet restrictions. With a 95% of confidence, our method can obtain quality adapted recipes without a previous knowledge extraction on the recipe adaptation domain. Our results confirm the potential of using a specific-domain semantic model to tackle the recipe adaptation task.es_ES
dc.description.sponsorshipEuropean Commission 816303es_ES
dc.description.sponsorshipUniversity of Granadaes_ES
dc.language.isoenges_ES
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCes_ES
dc.rightsAtribución 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectData mappinges_ES
dc.subjectFood computinges_ES
dc.subjectNatural language processinges_ES
dc.subjectRecipe adaptationes_ES
dc.subjectWord embeddinges_ES
dc.titleA Word Embedding-Based Method for Unsupervised Adaptation of Cooking Recipeses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.1109/ACCESS.2021.3058559


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Atribución 3.0 España
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