Attributions

[1] C. Pellegrini, E. Özsoy, M. Wintergerst, and G. Groh, “Exploiting Food Embeddings for Ingredient Substitution,” in Proc. 14th Int. Joint Conf. Biomed. Eng. Syst. Technol. (BIOSTEC 2021), vol. 5, HEALTHINF, pp. 67-77, 2021. DOI: 10.5220/0010202000670077.

[2] S. S. Shirai, O. Seneviratne, M. E. Gordon, C.-H. Chen, and D. L. McGuinness, “Identifying Ingredient Substitutions Using a Knowledge Graph of Food,” Frontiers in Artificial Intelligence, vol. 3, p. 621766, Jan. 2021. DOI: 10.3389/frai.2020.621766.

[3] J. Loesch et al., “Automated Identification of Healthier Food Substitutions Through a Combination of Graph Neural Networks and Nutri-Scores,” J. Food Composition and Analysis, vol. 125, p. 105829, Nov. 2023. DOI: 10.1016/j.jfca.2023.105829.

[4] M. Goel and G. Bagler, “Computational Gastronomy: A Data Science Approach to Food,” J. Biosci., vol. 47, p. 12, 2022. DOI: 10.1007/s12038-021-00248-1.

[5] H. Neelam and K. S. Veerella, “Enhancing Personalized Recipe Recommendation Through Multi-Class Classification,” Int. J. Comput. Sci. Eng. Inf. Technol., vol. 14, no. 5, pp. 15-25, Aug. 2024. DOI: 10.5121/ijcseit.2024.14502.

[6] A. Morales-Garzón, K. Gutiérrez-Batista, and M. J. Martin-Bautista, “Adaptafood: An Intelligent System to Adapt Recipes to Specialized Diets and Healthy Lifestyles,” Multimedia Systems, vol. 31, p. 87, 2025. DOI: 10.1007/s00530-025-01667-y.

[7] M. Kazama, M. Sugimoto, C. Hosokawa, K. Matsushima, L. R. Varshney, and Y. Ishikawa, “A Neural Network System for Transformation of Regional Cuisine Style,” Frontiers in ICT, vol. 5, 2018. Available: https://doi.org/10.3389/fict.2018.00014.

[8] M. De Clercq, M. Stock, B. De Baets, and W. Waegeman, “Data-Driven Recipe Completion Using Machine Learning Methods,” Trends in Food Science & Technology, vol. 49, pp. 1-13, 2016.

[9] N. Sakib et al., “Towards Automated Recipe Genre Classification Using Semi-Supervised Learning,” PLOS ONE, vol. 20, no. 1, e0317697, Jan. 2025.

[10] A. Lunterova, O. Spetko, and G. Palamas, “Explorative Visualization of Food Data to Raise Awareness of Nutritional Value,” in HCII 2019, LNCS 11786, Springer, pp. 180-191, 2019.

[11] J. Freyne, S. Berkovsky, and G. Smith, “Recipe Recommendation: Accuracy and Reasoning,” in Proceedings of the International Conference on User Modeling, Adaptation, and Personalization (UMAP), LNCS 6787, pp. 99–110, Springer, 2011.

[12] A. Lawrynowicz, A. Wróblewska, W. T. Adrian, B. Kulczyński, and A. Gramza-Michalowska, “Food Recipe Ingredient Substitution Ontology Design Pattern,” Sensors, vol. 22, no. 3, pp. 1095, 2022.

[13] W. Min, S. Jiang, L. Liu, Y. Rui, and R. Jain, “A Survey on Food Computing,” ACM Computing Surveys, vol. 52, no. 5, pp. 92, 2019.

[14] Y.-Y. Ahn, S. E. Ahnert, J. P. Bagrow, and A.-L. Barabási, “Flavor Network and the Principles of Food Pairing,” Scientific Reports, vol. 1, p. 196, Dec. 2011. DOI: 10.1038/srep00196.

[15] M. Chang et al., “RecipeScape: An Interactive Tool for Analyzing Cooking Instructions at Scale,” Proc. CHI Conf. Human Factors in Computing Systems, 2018, pp. 451:1-451:10. DOI: 10.1145/3173574.3174025.

[16] M. F. Costabile and P. Buono, “Principles for Human-Centred Design of IR Interfaces,” Lecture notes in computer science, pp. 28–47, Jan. 2013, doi: 10.1007/978-3-642-36415-0_2.

[17] L. Liu et al., “An Interactive Food Recommendation System Using Reinforcement Learning,” Expert Systems With Applications, vol. 254, p. 124313, 2024. DOI: 10.1016/j.eswa.2024.124313.

[18] J. N. Bondevik, K. E. Bennin, Ö. Babur, and C. Ersch, “A Systematic Review on Food Recommender Systems,” Expert Systems With Applications, vol. 238, p. 122166, 2024. DOI: 10.1016/j.eswa.2023.122166.

[19] K. Venkat, “The Climate Change and Economic Impacts of Food Waste in the US,” Int. J. Food System Dynamics, vol. 2, no. 4, pp. 431-446, 2011.

[20] B. Walia and S. Sanders, “Curbing Food Waste: A Review of Recent Policy and Action in the USA,” Renewable Agriculture and Food Systems, vol. 34, no. 2, pp. 169-177, 2017.

[21] A. Cooper et al., “Use-Up Day and Flexible Recipes: Reducing Household Food Waste by Helping Families Prepare Food They Already Have,” Resources, Conservation & Recycling, vol. 194, pp. 106986, 2023.