Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/27435
Title: Multimodal Analysis of User-recipes Interactions.
Authors: Georgievska, Emilija
Stojanoska, Martina
Mishovska, Sanja
Eftimov, Tome
Trajanov, Dimitar 
Keywords: Food, Recipes, Interactions, Recommendations
Issue Date: 2022
Conference: HEALTHINF
Abstract: A good diet is essential for good health and nutrition, but also as a way of expressing and feeling good. Culinary and food recommender systems are becoming increasingly popular at a time when people are facing fast-paced lifestyles. In this paper, we are analysing interactions between users and recipes in order to make food recommendations based on their previous behaviour which would result in higher personalization for every single person. This also raises the question of whether people stick to what they know well or are open to new suggestions, or do personal recommendations lead to more homogeneity.
URI: http://hdl.handle.net/20.500.12188/27435
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers

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