Resumen

TINOCO-LARA, Martha; VILCHIS GARCIA, Juan Ignacio; VILLUENDAS-REY, Yenny  y  ARGUELLES, Amadeo. KraKen: Dietary Behavior and Preferences-based Food Recommender System. Comp. y Sist. [online]. 2024, vol.28, n.4, pp.1833-1845.  Epub 25-Mar-2025. ISSN 2007-9737.  https://doi.org/10.13053/cys-28-4-4969.

This study addresses a key objective of the Sustainable Development Goals of the United Nations: improving life expectancy and reducing the principal causes of mortality. In Mexico, the increasing prevalence of chronic diseases such as diabetes, obesity, and hypertension has significantly compromised quality of life. Given these challenges, there is a critical need for innovative technology-based solutions that promote healthier lifestyles. Our research aims to implement a novel recommendation algorithm to identify group users with similar behavioral patterns. Using these patterns, the algorithm generates tailored recommendations designed to consistently improve dietary habits, taking into account both individual and collective preferences. Data for this study were collected through an online survey targeting the Mexican population. The findings indicate a significant shift towards healthier eating behaviors and a greater willingness to embrace emerging technologies. These trends herald a promising future in which technological integration in health and wellness could substantially improve community health and nutrition.

Palabras llave : Healthy eating; food recommendation; recommender algorithm; intelligent computing; artificial intelligence; food recommender system.

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