A prototype of a RBES for personalized menus generation

Eugenio Roanes-Lozano, José Luis Galán-García and Gabriel Aguilera-Venegas

Applied Mathematics and Computation, 2017, vol. 315, issue C, 615-624

Abstract: People have many constraints concerning the food they eat. These constraints can be based on religious believes, be due to food allergies or illnesses, or be derived from personal preferences or dislikes. For instance, preparing the menus at a hospital can be really complex. Another special situation arises when traveling abroad or simply when eating at a foreign cuisine restaurant (it is not always enough to know the brief description in the restaurant’s menu or the explanation of the waiter). Therefore, we consider that it would be very interesting to develop a knowledge-based system that automatically obtained a personalized menu for each customer, according to the precise recipes of the restaurant and taking into account the data given by the customer and the ingredients out of stock (if any). Although there are many knowledge-based systems devoted to diabetic’s meals, diets, food supply chains, etc., we do not know of any comparable system. We have developed a rule based expert system that uses sets and lists for handling data and an algebraic inference engine. It has been implemented in the computer algebra system Maple.

Keywords: Knowledge-based systems; Restaurant menus; Computer algebra; Groebner bases (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:315:y:2017:i:c:p:615-624

DOI: 10.1016/j.amc.2016.12.023

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