How Tasty Is This Dish? Studying User-Recipe Interactions with a Rating Prediction Algorithm and Graph Neural Networks
Authors: 
Andrea Morales-Garzón, Roberto Morcillo-Jimenez, Karel Gutiérrez-Batista, Maria J. Martin-BautistaAuthors Info & Claims
Andrea Morales-Garzón, Roberto Morcillo-Jimenez, Karel Gutiérrez-Batista, Maria J. Martin-BautistaAuthors Info & ClaimsPages 107 - 117
Abstract
Food computing has gained significant attention in recent years due to its direct relation to our health, habits, and cultural traditions. Food-related data have been extensively studied, and graph-based solutions have emerged to combine user-recipe data for various purposes, such as recipe recommendation and food-data alignment tasks. In this study, we propose a graph-based approach to predict the rating a specific user would give a recipe, harnessing the structured form of user-recipe interaction data. The approach incorporates two additional features into the user-recipe interactions graph: 1) user-recipe review embeddings generated by a sentence-based transformer model and 2) a selection of healthy recipe features inferred from nutritional content and international nutrition standards. Results obtained from experiments on a publicly available dataset demonstrate that the proposed method achieves competitive performance compared to recent advancements.
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Information & Contributors
Information
Published In
Sep 2023
315 pages
ISBN:978-3-031-42934-7
DOI:10.1007/978-3-031-42935-4
© Springer Nature Switzerland AG 2023.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 07 September 2023
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