Publication
AquaVitae: Innovating Personalized Meal Recommendations for Enhanced Nutritional Health
| dc.contributor.author | Marcuzzo, Henrique S. | |
| dc.contributor.author | Pereira, Maria J. V. | |
| dc.contributor.author | Alves, Paulo | |
| dc.contributor.author | Foleis, Juliano H. | |
| dc.date.accessioned | 2024-10-08T10:10:41Z | |
| dc.date.available | 2024-10-08T10:10:41Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | In this study, we present an advanced recommendation system specifically engineered to aid nutritionists in developing personalized, optimized nutritional plans. Our system operates by amassing a broad range of data including users’ preferences, dietary restrictions, and specific nutritional requirements, which it then utilizes to craft a diverse assortment of meal choices individually tailored to each user. A key innovation of our system is its ability to facilitate continuous diet monitoring, eliminating the need for repeated consultations to update the nutritional plans. This allows for real-time dietary adjustments and provides nutritionists with more accurate data for subsequent plans. Additionally, the system prioritizes the inclusion of thermogenic foods to maximize nutritional efficiency, while simultaneously providing a pleasurable experience for the users. This combination of sophisticated data collection and innovative food recommendations underscores the potential of our system to improve the process of nutritional counseling and the generation of nutritional plans, bringing notable benefits to both practitioners and clients alike. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Marcuzzo, Henrique S.; Pereira, Maria J. V.; Alves, Paulo; Foleis, Juliano H. (2024). AquaVitae: Innovating Personalized Meal Recommendations for Enhanced Nutritional Health. In 3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023). Cham: Springer Nature, Vol. 1, p. 148–161. ISBN 978-3-031-53024-1 | pt_PT |
| dc.identifier.doi | 10.1007/978-3-031-53025-8_11 | pt_PT |
| dc.identifier.isbn | 978-3-031-53024-1 | |
| dc.identifier.isbn | 978-3-031-53025-8 | |
| dc.identifier.uri | http://hdl.handle.net/10198/30355 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Springer Nature | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Recommendation System | pt_PT |
| dc.subject | Thermal-Based | pt_PT |
| dc.subject | Nutritional Plan | pt_PT |
| dc.subject | Food Ranking | pt_PT |
| dc.title | AquaVitae: Innovating Personalized Meal Recommendations for Enhanced Nutritional Health | pt_PT |
| dc.type | conference paper | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 161 | pt_PT |
| oaire.citation.startPage | 148 | pt_PT |
| oaire.citation.title | 3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023) | pt_PT |
| person.familyName | Alves | |
| person.givenName | Paulo | |
| person.identifier.ciencia-id | C319-FC42-5B6B | |
| person.identifier.orcid | 0000-0002-0100-8691 | |
| person.identifier.scopus-author-id | 55834442100 | |
| rcaap.rights | restrictedAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
| relation.isAuthorOfPublication | 43d3b0cd-8fd9-4194-a9df-9cca66f8726b | |
| relation.isAuthorOfPublication.latestForDiscovery | 43d3b0cd-8fd9-4194-a9df-9cca66f8726b |