{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T21:20:04Z","timestamp":1775856004286,"version":"3.50.1"},"reference-count":28,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T00:00:00Z","timestamp":1641859200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100007434","name":"Agencia de Inovacao","doi-asserted-by":"publisher","award":["Future Y\u00e4mmi"],"award-info":[{"award-number":["Future Y\u00e4mmi"]}],"id":[{"id":"10.13039\/501100007434","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","doi-asserted-by":"publisher","award":["CEECIND\/03988\/2018"],"award-info":[{"award-number":["CEECIND\/03988\/2018"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>Nutrition is an essential part of our life. A healthy diet can help to prevent several chronic diseases like diabetes, obesity, cancer, and cardiovascular diseases, being influenced by social, cultural, and economic factors. Meal recommender systems are a trend to assist people in finding new recipes to cook and adopt healthier eating habits. However, food choice is complex and driven by multiple factors which need to be reflected in the personalization process of these systems to ensure their adoption. We present SousChef, a meal recommender system that can help to plan multiple meals considering an individual\u2019s food preferences, restrictions, and nutritional needs. Our approach uses recipes rather than individual food items, limiting recommendations to tasteful and culturally acceptable food combinations. Several experiments were performed to evaluate the system from different perspectives: nutritional, food preferences, and restrictions, and the recommendations\u2019 variability. Our results highlight the importance of using extensive and diverse content in recommendations to meet food preferences, restrictions, and nutritional needs of people with different characteristics.<\/jats:p>","DOI":"10.3390\/app12020702","type":"journal-article","created":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T14:05:07Z","timestamp":1641909907000},"page":"702","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["SousChef System for Personalized Meal Recommendations: A Validation Study"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0001-4456","authenticated-orcid":false,"given":"David","family":"Ribeiro","sequence":"first","affiliation":[{"name":"Fraunhofer Portugal AICOS, 4200-135 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9211-8900","authenticated-orcid":false,"given":"Telmo","family":"Barbosa","sequence":"additional","affiliation":[{"name":"Fraunhofer Portugal AICOS, 4200-135 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5532-2574","authenticated-orcid":false,"given":"Jorge","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"Fraunhofer Portugal AICOS, 4200-135 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8278-9062","authenticated-orcid":false,"given":"Filipe","family":"Sousa","sequence":"additional","affiliation":[{"name":"Fraunhofer Portugal AICOS, 4200-135 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0301-6182","authenticated-orcid":false,"given":"Elsa F.","family":"Vieira","sequence":"additional","affiliation":[{"name":"REQUIMTE\/LAQV, Institute of Engineering of Porto, Polytechnic Institute of Porto, 4249-015 Porto, Portugal"}]},{"given":"Marlos","family":"Silva","sequence":"additional","affiliation":[{"name":"Sonae MC Servi\u00e7os Partilhados, 4470-177 Maia, Portugal"}]},{"given":"Ana","family":"Silva","sequence":"additional","affiliation":[{"name":"Sonae MC Servi\u00e7os Partilhados, 4470-177 Maia, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,11]]},"reference":[{"key":"ref_1","unstructured":"WHO (2021, December 09). Diet, Nutrition and the Prevention of Chronic Diseases. Available online: https:\/\/www.who.int\/dietphysicalactivity\/publications\/trs916\/en\/."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1007\/s10844-020-00633-6","article-title":"Recommender Systems in the Healthcare Domain: State-of-the-Art and Research Issues","volume":"57","author":"Tran","year":"2020","journal-title":"J. Intell. Inf. Syst."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Zadeh, M.S.A.T., Li, J., and Alian, S. (2019, January 14\u201316). Personalized Meal Planning for Diabetic Patients Using a Multi-Criteria Decision-Making Approach. Proceedings of the 2019 IEEE International Conference on E-Health Networking, Application Services (HealthCom), Bogota, Colombia.","DOI":"10.1109\/HealthCom46333.2019.9009593"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Sapri, N.S.M., Bedi, M.R., Abdul-Rahman, S., and Benjamin, A.M. (2019, January 25\u201328). A Diet Recommendation for Diabetic Patients Using Integer Programming. Proceedings of the 4th Innovation and Analytics Conference & Exhibition Iace, Kedah, Malaysia.","DOI":"10.1063\/1.5121101"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Ribeiro, D., Machado, J., Vasconcelos, M.J.M., Vieira, E., and Correia de Barros, A. (2017, January 28\u201329). SousChef: Mobile Meal Recommender System for Older Adults. Proceedings of the 3rd International Conference on Information and Communication Technologies for Ageing Well and E-Health, SCITEPRESS, Porto, Portugal.","DOI":"10.5220\/0006281900360045"},{"key":"ref_6","unstructured":"R\u00f6cker, C., O\u2019Donoghue, J., Ziefle, M., Maciaszek, L., and Molloy, W. (2018). SousChef: Improved Meal Recommender System for Portuguese Older Adults. Information and Communication Technologies for Ageing Well and E-Health, Springer International Publishing. Communications in Computer and Information Science."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Ribeiro, J., Ribeiro, D., Schwarz, A., Vasconcelos, M.J.M., Gerardo, F., van Harten, C., Succu, R., Davison, R., Oliveira, T., and Silva, T. (2018, January 19\u201323). Cordon Gris: Integrated Solution for Meal Recommendations. Proceedings of the 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Athens, Greece.","DOI":"10.1109\/PERCOMW.2018.8480404"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Pecune, F., Callebert, L., and Marsella, S. (2020, January 26). A Recommender System for Healthy and Personalized Recipe Recommendations. Proceedings of the CEUR Workshop Proceedings, CEUR-WS, Online.","DOI":"10.1145\/3406499.3415079"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"28462","DOI":"10.1109\/ACCESS.2020.2968537","article-title":"Realizing an Efficient IoMT-Assisted Patient Diet Recommendation System Through Machine Learning Model","volume":"8","author":"Iwendi","year":"2020","journal-title":"IEEE Access"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Thampi, S.M., Trajkovic, L., Li, K.C., Das, S., Wozniak, M., and Berretti, S. (2020). QuicklyCook: A User-Friendly Recipe Recommender. Machine Learning and Metaheuristics Algorithms, and Applications, Springer. Communications in Computer and Information Science.","DOI":"10.1007\/978-981-15-4301-2"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Tangseng, P., Yamaguchi, K., and Okatani, T. (2017, January 22\u201329). Recommending Outfits from Personal Closet. Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops (ICCVW), Venice, Italy.","DOI":"10.1109\/ICCVW.2017.267"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Lamche, B., Trottmann, U., and W\u00f6rndl, W. (2014, January 13). Active Learning Strategies for Exploratory Mobile Recommender Systems. Proceedings of the 4th Workshop on Context-Awareness in Retrieval and Recommendation (CARR \u201914), Amsterdam, The Netherlands.","DOI":"10.1145\/2601301.2601304"},{"key":"ref_13","unstructured":"Pham, H. (2020). Integrating Sentiment Analysis in Recommender Systems. Reliability and Statistical Computing: Modeling, Methods and Applications, Springer International Publishing."},{"key":"ref_14","unstructured":"Lamche, B., Pollok, E., W\u00f6rndl, W., and Groh, G. (2014, January 7\u201311). Evaluating the Effectiveness of Stereotype User Models for Recommendations on Mobile Devices. Proceedings of the Joint Workshop on Personalized Information Access (PIA 2014), in Conjunction with the 22nd Conference on User Modeling, Adaptation and Personalization (UMAP 2014), Aalborg, Denmark."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1647","DOI":"10.1109\/TMM.2019.2945180","article-title":"Hierarchical Attention Network for Visually-Aware Food Recommendation","volume":"22","author":"Gao","year":"2020","journal-title":"IEEE Trans. Multimed."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Bundasak, S., and Chinnasarn, K. (2013, January 29\u201331). eMenu Recommender System Using Collaborative Filtering and Slope One Predictor. Proceedings of the 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE), Khon Kaen, Thailand.","DOI":"10.1109\/JCSSE.2013.6567316"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"96695","DOI":"10.1109\/ACCESS.2019.2929413","article-title":"A Food Recommender System Considering Nutritional Information and User Preferences","volume":"7","author":"Alzahrani","year":"2019","journal-title":"IEEE Access"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Sowah, R.A., Bampoe-Addo, A.A., Armoo, S.K., Saalia, F.K., Gatsi, F., and Sarkodie-Mensah, B. (2021, December 09). Design and Development of Diabetes Management System Using Machine Learning. Available online: https:\/\/www.hindawi.com\/journals\/ijta\/2020\/8870141\/.","DOI":"10.1155\/2020\/8870141"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Chillarige, R.R., Distefano, S., and Rawat, S.S. (2020). Recommendation of Diet Using Hybrid Collaborative Filtering Learning Methods. Advances in Computational Intelligence and Informatics, Springer. Lecture Notes in Networks and Systems.","DOI":"10.1007\/978-981-15-3338-9"},{"key":"ref_20","first-page":"2910","article-title":"Diet-Right: A Smart Food Recommendation System","volume":"11","author":"Rehman","year":"2017","journal-title":"KSII Trans. Internet Inf. Syst."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Shani, G., and Gunawardana, A. (2011). Evaluating Recommendation Systems. Recommender Systems Handbook, Springer.","DOI":"10.1007\/978-0-387-85820-3_8"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"734","DOI":"10.1109\/TKDE.2005.99","article-title":"Toward the next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions","volume":"17","author":"Adomavicius","year":"2005","journal-title":"Knowl. Data Eng. IEEE Trans."},{"key":"ref_23","unstructured":"Schr\u00f6der, G., Thiele, M., and Lehner, W. (2011, January 23\u201327). Setting Goals and Choosing Metrics for Recommender System Evaluations. Proceedings of the UCERSTI2 Workshop at the 5th ACM Conference on Recommender Systems, Chicago, IL, USA."},{"key":"ref_24","unstructured":"Instituto Nacional de Sa\u00fade Dr. Ricardo Jorge (2021, December 09). Tabela de Composi\u00e7\u00e3o Dos Alimentos. Available online: http:\/\/portfir.insa.pt\/foodcomp\/introduction."},{"key":"ref_25","unstructured":"M\u00f8ller, A., and Ireland, J. (2018). LanguaL\u2122 2017-Thesaurus, EuroFIR. Technical Report, Danish Food Informatics."},{"key":"ref_26","unstructured":"Lopes, C., Torres, D., Oliveira, A., Severo, M., Alarc\u00e3o, V., Guiomar, S., Mota, J., Teixeira, P., Rodrigues, S., and Lobato, L. (2017). Inqu\u00e9rito Alimentar Nacional e de Atividade F\u00edsica IAN-AF 2015\u20132016: Relat\u00f3rio Parte II, University of Porto. Methodological Report."},{"key":"ref_27","unstructured":"Institute of Medicine (2005). Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids, The National Academies Press."},{"key":"ref_28","unstructured":"U.S. Department of Health and Human Services, and U.S. Department of Agriculture (2021, December 09). 2015\u20132020 Dietary Guidelines for Americans, Available online: https:\/\/health.gov\/our-work\/food-nutrition\/previous-dietary-guidelines\/2015."}],"container-title":["Applied Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-3417\/12\/2\/702\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:27:15Z","timestamp":1760362035000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-3417\/12\/2\/702"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,11]]},"references-count":28,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["app12020702"],"URL":"https:\/\/doi.org\/10.3390\/app12020702","relation":{},"ISSN":["2076-3417"],"issn-type":[{"value":"2076-3417","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,11]]}}}