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- W3126149574 abstract "Poor dietary behaviours are commonly associated with severe chronic diseases such as cardiovascular diseases, diabetes and obesity. Personalized food recommendation systems can be an important motivation to stimulate and inform people on best dietary practices by suggesting healthy foods and nutritionally balanced meals adjusted to their preferences and daily routines. The development of such systems require the process and integration of data available from different sources with different representations. FILLET is an intelligent platform for nutrition capable of collecting and integrating data from multiple sources including recipe websites, food blogs and nutrition databases. Components were developed for web scraping, identifying ingredients, estimating nutritional content and matching ingredients with food products from retailers to support a meal recommendation and shopping list assistance services. We present for each component the challenges identified in the literature and the ones we faced in their development, describing our approach and the lessons learned that can contribute to the future improvement of the platform and the development of related platforms." @default.
- W3126149574 created "2021-02-15" @default.
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- W3126149574 date "2020-11-01" @default.
- W3126149574 modified "2023-10-14" @default.
- W3126149574 title "FILLET - Platform for Intelligent Nutrition" @default.
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- W3126149574 doi "https://doi.org/10.1109/aiccsa50499.2020.9316490" @default.
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