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On the Relations Between Cooking Interests, Hobbies and Nutritional Values of Online Recipes: Implications for Health-Aware Recipe Recommender Systems

Published: 09 July 2017 Publication History

Abstract

In this paper, we investigate differences between recipes uploaded by users and recipes bookmarked by users. The results indicate that uploaded recipes outperform bookmarked recipes in terms of healthiness. Further, health scores and nutritional values of these recipes are highly related to the stated cooking interests: for example, Southern Food lovers eat not as healthy as those who prefer the Mediterranean or Middle-Eastern cuisine. A disturbing finding is that interest in the category `Kids' is associated with bad values for all nutritional measures. We also found some interactions between hobbies such as biking, hunting or knitting and nutritional values. These insights pave way to the design of health-aware recipe recommender systems that take a user's food preferences into account; in addition, taking a user's lifestyle and hobbies into account would provide valuable input to persuasive systems.

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      cover image ACM Conferences
      UMAP '17: Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization
      July 2017
      456 pages
      ISBN:9781450350679
      DOI:10.1145/3099023
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 09 July 2017

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      Author Tags

      1. cooking interests
      2. food preferences
      3. hobbies
      4. nutrition
      5. online recipes

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      • (2023)Understanding and predicting cross-cultural food preferences with online recipe imagesInformation Processing & Management10.1016/j.ipm.2023.10344360:5(103443)Online publication date: Sep-2023
      • (2023)Research on Food Recommendation Method Based on Knowledge GraphComputer Science and Education10.1007/978-981-99-2443-1_45(521-533)Online publication date: 14-May-2023
      • (2023)“Health Is the Real Wealth”: Unsupervised Approach to Improve Explainability in Health-Based Recommendation SystemsFlexible Query Answering Systems10.1007/978-3-031-42935-4_19(234-246)Online publication date: 7-Sep-2023
      • (2022)A Survey on Healthy Food Decision Influences Through Technological InnovationsACM Transactions on Computing for Healthcare10.1145/34945803:2(1-27)Online publication date: 3-Mar-2022
      • (2022)Food recognition via an efficient neural network with transformer groupingInternational Journal of Intelligent Systems10.1002/int.2305037:12(11465-11481)Online publication date: 2-Sep-2022
      • (2021)Social Media Mining for an Analysis of Nutrition and Dietary Health in TaiwanNutrients10.3390/nu1306177813:6(1778)Online publication date: 23-May-2021
      • (2021)Mapping the digital food environment: A systematic scoping reviewObesity Reviews10.1111/obr.1335623:1Online publication date: 14-Sep-2021
      • (2021)Addressing the complexity of personalized, context-aware and health-aware food recommendations: an ensemble topic modelling based approachJournal of Intelligent Information Systems10.1007/s10844-021-00639-8Online publication date: 12-May-2021
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      • (2020)Neural Restaurant-aware Dish Recommendation2020 IEEE International Conference on Knowledge Graph (ICKG)10.1109/ICBK50248.2020.00090(599-606)Online publication date: Aug-2020
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