Abstract
Lifestyle, poor diet, stress, among other factors, strongly contribute to aggravate people’s health problems, such as diabetes and high blood pressure. Some of these problems could be avoided if some of the essential recommendations for the practice of a healthy lifestyle were followed. The paper proposes a solution designed for diabetic people to find restaurants nearby that are more suitable for their health needs. A diabetic-friendly feature that will use a set of criteria, built through a Multi-Agent System (MAS) that using the user preferences initially recorded, will provide the user with three category recommendations that potentially benefit the user lifestyle and health. The solution proposes the use of Case-Based Reasoning algorithm to enable the solution to evolve and improve in each interaction with the user. Sentiment Analysis was also used for identifying the restaurant reviews score, since this is one of the defined criteria for the solution.
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Acknowledgments
This research work was developed under the project Food Friend –”Autonomous and easy-to-use tool for monitoring of personal food intake and personalized feedback” (ITEA 18032), co-financed by the North Regional Operational Program (NORTE 2020) under the Portugal 2020 and the European Regional Development Fund (ERDF), with the reference NORTE-01-0247-FEDER-047381 and by National Funds through FCT (Fundação para a Ciência e a Tecnologia) under the project UI/DB/00760/2020.
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Teixeira, B., Martinho, D., Novais, P., Corchado, J., Marreiros, G. (2022). Diabetic-Friendly Multi-agent Recommendation System for Restaurants Based on Social Media Sentiment Analysis and Multi-criteria Decision Making. In: Marreiros, G., Martins, B., Paiva, A., Ribeiro, B., Sardinha, A. (eds) Progress in Artificial Intelligence. EPIA 2022. Lecture Notes in Computer Science(), vol 13566. Springer, Cham. https://doi.org/10.1007/978-3-031-16474-3_30
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