Publication
Unveiling Neural Networks for Personalized Diet Recommendations
| dc.contributor.author | Cunha, Carlos | |
| dc.contributor.author | Rebelo, João | |
| dc.contributor.author | P. Duarte, Rui | |
| dc.date.accessioned | 2024-10-15T09:56:18Z | |
| dc.date.available | 2024-10-15T09:56:18Z | |
| dc.date.issued | 2024 | |
| dc.date.updated | 2024-09-21T23:42:01Z | |
| dc.description.abstract | The growing prevalence of poor nutrition is a major public health concern, as it fuels the rise of various diseases. Obesity, a silent and rapidly growing threat linked to unhealthy eating, is a prime example. Despite the abundance of information on diets and recipes, finding a personalized approach to healthy eating can be a challenge. Recommendation systems can filter from a food logging dataset the information that best suits the nutrition profile of a given user. A powerful tool to use in food recommendation systems is neural networks. However, the user’s available data are often limited, which compromises the performance of neural-based food recommendation models. To enhance user trust in food recommendations, this paper proposes a method using a secondary model to predict the errors of the primary neural network, especially when dealing with limited data. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.1016/j.procs.2024.08.088 | pt_PT |
| dc.identifier.issn | 1877-0509 | |
| dc.identifier.slug | cv-prod-4150561 | |
| dc.identifier.uri | http://hdl.handle.net/10400.19/8597 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.relation | PIDI/CISeD/2022/007 | pt_PT |
| dc.subject | Personalized Nutrition | pt_PT |
| dc.subject | Error Prediction | pt_PT |
| dc.subject | Machine Learning | pt_PT |
| dc.title | Unveiling Neural Networks for Personalized Diet Recommendations | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 611 | pt_PT |
| oaire.citation.startPage | 606 | pt_PT |
| oaire.citation.title | Procedia Computer Science | pt_PT |
| oaire.citation.volume | 241 | pt_PT |
| person.familyName | Cunha | |
| person.familyName | Monteiro Amaro Duarte | |
| person.givenName | Carlos | |
| person.givenName | Rui Pedro | |
| person.identifier | 2081924 | |
| person.identifier | gIYE8M4AAAAJ | |
| person.identifier.ciencia-id | D71F-FC65-1F07 | |
| person.identifier.ciencia-id | 211F-55A0-4B63 | |
| person.identifier.orcid | 0000-0002-2754-5401 | |
| person.identifier.orcid | 0000-0002-6819-0985 | |
| person.identifier.scopus-author-id | 39361170900 | |
| person.identifier.scopus-author-id | 14059938600 | |
| rcaap.cv.cienciaid | 211F-55A0-4B63 | Rui Pedro Monteiro Amaro Duarte | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | 384f50cd-9e87-40bd-b610-58008e05bec1 | |
| relation.isAuthorOfPublication | d56c3162-80a4-4ade-810d-43bae4ee6d73 | |
| relation.isAuthorOfPublication.latestForDiscovery | 384f50cd-9e87-40bd-b610-58008e05bec1 |