Design of personalized nutritional meal recommendation system driven by big data
Bo Pang
Beijing Forestry University
DOI: https://doi.org/10.59429/esta.v11i4.8469
Keywords: Big data analytics; Personalized nutrition meals; User profiling; Nutrition model; Recommendation algorithm
Abstract
In the context of the continuous development of big data technology, personalized nutritional meal recommendation systems have become an important means for people to their eating habits and enhance their quality of life. The purpose of this study is to design a personalized nutritional meal recommendation system based on big data analysis to meet users healthy eating needs. The system collects and analyzes data on users’ dietary preferences, health status, and lifestyle habits to build user profiles. It then combines a food database with a nutritional needs calculation model, using improved content-based recommendation algorithms: collaborative filtering algorithm and hybrid recommendation algorithm, to provide users with personalized nutritional meal recommendations The system design is user-centered, aiming for precise recommendations and using technical means to promote healthy eating habits among the general public.
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