Recommendation systems have been developed to address the immense volume of information accessible on the Internet. These systems employ filtering methodologies and customize their recommendations by drawing insights from user profiles, ultimately enhancing the relevance and utility of their suggestions. In this paper, we present our system called Smart Food and Restaurant Advisor based on nutritional needs and user profiling (SFRA); a multi-criteria food and restaurant recommendation system designed to prioritize personalized and health-conscious selections. This system uses user profiling to offer customized recommendations that cater to individual preferences, requirements, and geographic locations. Our primary objective is to enhance users’ decision-making processes by promoting healthier and more refined lifestyle choices. The results of the proposed system demonstrate that it is well-suited for promoting a healthier lifestyle while offering comprehensive coverage of users’ practices and preferences.

A Multi-Criteria Food and Restaurant Recommendation System

Guerrieri, Antonio;
2024

Abstract

Recommendation systems have been developed to address the immense volume of information accessible on the Internet. These systems employ filtering methodologies and customize their recommendations by drawing insights from user profiles, ultimately enhancing the relevance and utility of their suggestions. In this paper, we present our system called Smart Food and Restaurant Advisor based on nutritional needs and user profiling (SFRA); a multi-criteria food and restaurant recommendation system designed to prioritize personalized and health-conscious selections. This system uses user profiling to offer customized recommendations that cater to individual preferences, requirements, and geographic locations. Our primary objective is to enhance users’ decision-making processes by promoting healthier and more refined lifestyle choices. The results of the proposed system demonstrate that it is well-suited for promoting a healthier lifestyle while offering comprehensive coverage of users’ practices and preferences.
2024
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Big data analytic
Food and restaurant recommendation
Machine learning
Multi-criteria methods
personalized recommendations
Recommendation system
user profiling
File in questo prodotto:
File Dimensione Formato  
RXX 2024 Nawel Food.pdf

solo utenti autorizzati

Licenza: Altro tipo di licenza
Dimensione 1.52 MB
Formato Adobe PDF
1.52 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/522728
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact