Ir al contenido

Documat


Combining data-driven and domain knowledge components in an intelligent assistant to build personalized menus

  • Autores: Miquel Sànchez i Marrè Árbol académico, Karina Gibert Oliveras Árbol académico, Beatriz Sevilla Villanueva
  • Localización: From Bioinspired Systems and Biomedical Applications to Machine Learning: 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019, Almería, Spain, June 3–7, 2019, Proceedings, Part II / coord. por Hojjat Adeli; José Manuel Ferrández Vicente (dir. congr.) Árbol académico, José Ramón Álvarez Sánchez (dir. congr.) Árbol académico, Félix de la Paz López (dir. congr.) Árbol académico, Francisco Javier Toledo Moreo (dir. congr.), 2019, ISBN 978-3-030-19651-6, págs. 167-179
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • In this paper, some new components that have been integratedin the Diet4You system for the generation of nutritional plansare introduced. Negative user preferences have been modelled and introduced in the system. Furthermore, the cultural eating styles originated from the location where the user lives have been taken into account dividing the original menu plan in sub-plans. Each sub-plan is in charge to optimize one of the meals of one day in the personal menu of the user. The main latent reasoning mechanism used is case-based reasoning, which reuses previous menu configurations according to the nutritional plan and the corresponding hard constraints and the user preferences tomeet a personalized recommendation menu for a given user. It uses the cognitive analogical reasoning technique in addition to ontologies, nutritional databases and expert knowledge. The preliminary results with some examples of application to test the new contextual components have been very satisfactory according to the evaluation of the experts


Fundación Dialnet

Mi Documat

Opciones de artículo

Opciones de compartir

Opciones de entorno