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Registro Completo |
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
07/06/2022 |
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Data da última atualização: |
16/08/2022 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
ALVES, R. das D.; DAVID, J. M.; BRAGA, R.; SIQUEIRA, K. B.; BARBOSA, G.; COSTA, J. P.; STROELE, V.; BARRERE, E. |
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Afiliação: |
RIAN DAS DORES ALVES, Universidade Federal de Juiz de Fora; JOSE MARIA DAVID, Universidade Federal de Juiz de Fora; REGINA BRAGA, Universidade Federal de Juiz de Fora; KENNYA BEATRIZ SIQUEIRA, CNPGL; GUILHERME BARBOSA, Universidade Federal de Juiz de Fora; JOAO P. COSTA, Universidade Federal de Juiz de Fora; VICTOR STROELE, Universidade Federal de Juiz de Fora; EDUARDO BARRERE, Universidade Federal de Juiz de Fora. |
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Título: |
An architecture for food product recommendation focusing on nutrients and price. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
In: CAISE FORUM, 34., 2022, Leuven. Intelligent information systems: proceedings. Cham: Springer, 2022. |
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DOI: |
https://doi.org/10.1007/978-3-031-07481-3_1 |
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Idioma: |
Inglês |
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Conteúdo: |
Part of the world?s population is nutrient deficient, a phenomenon known as hidden hunger. Poor eating conditions cause this deficiency, leading to illnesses and recovery difficulties. Malnourished patients are more easily affected by Covid-19 and have a difficult recovery after the illness. An effective food choice has the price and nutritional value of food products as the most relevant factors, with the price being the most relevant, considering the context of countries such as Brazil. Thus, having identified a scenario in which the access and food price mainly cause malnutrition. This work proposes an architecture, called Nutri?n Price, to recommend high nutritional foods with low costs. The architecture encompasses a network of ontologies, inference algorithms, information retrieval and collaborative filtering techniques to recommend the best foods according to nutrient choice, price, and user contextual information. A prototype of a mobile application was developed to evaluate the feasibility of the proposed architecture. |
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Palavras-Chave: |
Nutri’n Price; Recuperação da informação; Rede de ontologias. |
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Thesagro: |
Alimento; Preço; Produto Derivado do Leite; Valor Nutritivo. |
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Categoria do assunto: |
Q Alimentos e Nutrição Humana |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1143822/1/Architecture-for-food-product-recommendation.pdf
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Marc: |
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001 2143822
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008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/978-3-031-07481-3_1$2DOI
100 1 $aALVES, R. das D.
245 $aAn architecture for food product recommendation focusing on nutrients and price.$h[electronic resource]
260 $aIn: CAISE FORUM, 34., 2022, Leuven. Intelligent information systems: proceedings. Cham: Springer$c2022
520 $aPart of the world?s population is nutrient deficient, a phenomenon known as hidden hunger. Poor eating conditions cause this deficiency, leading to illnesses and recovery difficulties. Malnourished patients are more easily affected by Covid-19 and have a difficult recovery after the illness. An effective food choice has the price and nutritional value of food products as the most relevant factors, with the price being the most relevant, considering the context of countries such as Brazil. Thus, having identified a scenario in which the access and food price mainly cause malnutrition. This work proposes an architecture, called Nutri?n Price, to recommend high nutritional foods with low costs. The architecture encompasses a network of ontologies, inference algorithms, information retrieval and collaborative filtering techniques to recommend the best foods according to nutrient choice, price, and user contextual information. A prototype of a mobile application was developed to evaluate the feasibility of the proposed architecture.
650 $aAlimento
650 $aPreço
650 $aProduto Derivado do Leite
650 $aValor Nutritivo
653 $aNutri’n Price
653 $aRecuperação da informação
653 $aRede de ontologias
700 1 $aDAVID, J. M.
700 1 $aBRAGA, R.
700 1 $aSIQUEIRA, K. B.
700 1 $aBARBOSA, G.
700 1 $aCOSTA, J. P.
700 1 $aSTROELE, V.
700 1 $aBARRERE, E.
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Registro original: |
Embrapa Gado de Leite (CNPGL) |
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| 1. |  | ALVES, R. das D.; DAVID, J. M.; BRAGA, R.; SIQUEIRA, K. B.; BARBOSA, G.; COSTA, J. P.; STROELE, V.; BARRERE, E. An architecture for food product recommendation focusing on nutrients and price. In: CAISE FORUM, 34., 2022, Leuven. Intelligent information systems: proceedings. Cham: Springer, 2022.| Tipo: Artigo em Anais de Congresso |
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