Food Recommendation System Based on Data Clustering Techniques and User Nutrition Records-Reference-Cited by-同舟云学术

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Food Recommendation System Based on Data Clustering Techniques and User Nutrition Records

Published:2023 Issue: Volume: Page:139-161
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
Short-container-title:

Author:

Al-Chalabi Hayder Hussein,Jasim Mahdi Nsaif

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-35442-7_8

Reference41 articles.

1. Baek, J., Kim, J., Chun, J., Chung, K.: Hybrid clustering based health decision-making for improving dietary habits, vol. 1, pp. 1–14 (January 2019). https://doi.org/10.3233/THC-191730

2. Martinon, P., Fraticelli, L., Giboreau, A., Dussart, C., Bourgeois, D., Carrouel, F.: Nutrition as a key modifiable factor for periodontitis and main chronic diseases. J. Clin. Med. 10(2), 1–26 (2021). https://doi.org/10.3390/jcm10020197

3. Egan, A.M., Dinneen, S.F.: What is diabetes? Med. (United Kingdom) 47(1), 1–4 (2019). https://doi.org/10.1016/j.mpmed.2018.10.002

4. Heba Abdelgader Mohammed, H.H.: Towards Developing Type 2 Fuzzy Logic Diet Recommendation System for Diabetes. In: 2018 10th Computer Science and Electronic Engineering , pp. 56–59 (2018). https://doi.org/10.1109/CEEC.2018.8674186

5. Batta, M.: Machine learning algorithms - a review. Int. J. Sci. Res. (IJ, 9(1), 381–386 (2020). https://doi.org/10.21275/ART20203995

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1. Nutrition Recommendation System for Sports Persons using Random Forest Algorithm;2024 International Conference on Smart Systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC);2024-06-28

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