University of Oulu

A food recipe recommendation system based on nutritional factors in the Finnish food communit

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Author: Walpitage, Ashan1
Organizations: 1University of Oulu, Faculty of Information Technology and Electrical Engineering, Computer Science
Format: ebook
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.6 MB)
Pages: 52
Persistent link:
Language: English
Published: Oulu : A. Walpitage, 2023
Publish Date: 2023-06-30
Thesis type: Master's thesis (tech)
Tutor: Oussalah, Mourad
Reviewer: Partala, Juha
Oussalah, Mourad


This thesis presents a comprehensive study on the relationships between user feedback, recipe content, and additional factors in the context of a recipe recommendation system. The aim was to investigate the influence of various factors on user ratings and comments related to nutritional variables, while also exploring the potential for personalized recipe suggestions. Statistical analysis, clustering techniques, and sentiment analysis were employed to analyze a dataset of food recipes and user feedback. We determined that user feedback is a complex phenomenon influenced by subjective factors beyond recipe content alone. Cluster analysis identified four distinct clusters within the dataset, highlighting variations in nutritional values and sentiment among recipes. However, due to an imbalanced distribution within the clusters, these relationships were not considered in the recommendation system. To address the absence of user-related data, a content-based filtering approach was implemented, utilizing nutritional factors and a health factor calculation. The system provides personalized recipe recommendations based on nutritional similarity and health considerations. A maximum limit of 20 recommended recipes was set, allowing users to specify the desired number of recommendations. The accompanying API also provides a mean squared error metric to assess recommendation quality. This research contributes to a better understanding of user preferences, recipe content, and the challenges in developing effective recommendation systems for food recipes.

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Copyright information: © Ashan Walpitage, 2023. Except otherwise noted, the reuse of this document is authorised under a Creative Commons Attribution 4.0 International (CC-BY 4.0) licence ( This means that reuse is allowed provided appropriate credit is given and any changes are indicated. For any use or reproduction of elements that are not owned by the author(s), permission may need to be directly from the respective right holders.