- Autor
- Trang Tran, Thi Ngoc
- Atas, Müslüm
- Felfernig, Alexander
- Stettinger, Martin
- TitelAn overview of recommender systems in the healthy food domain
- Datei
- DOI10.1007/s10844-017-0469-0
- Persistent Identifier
- Erschienen inJournal of Intelligent Information Systems
- Band50
- Erscheinungsjahr2018
- Heft3
- Seiten501-526
- ISSN1573-7675
- Download Statistik1070
- Peer ReviewJa
- AbstractRecently, food recommender systems have received increasing attention due to their relevance for healthy living. Most existing studies on the food domain focus on recommendations that suggest proper food items for individual users on the basis of considering their preferences or health problems. These systems also provide functionalities to keep track of nutritional consumption as well as to persuade users to change their eating behavior in positive ways. Also, group recommendation functionalities are very useful in the food domain, especially when a group of users wants to have a dinner together at home or have a birthday party in a restaurant. Such scenarios create many challenges for food recommender systems since the preferences of all group members have to be taken into account in an adequate fashion. In this paper, we present an overview of recommendation techniques for individuals and groups in the healthy food domain. In addition, we analyze the existing state-of-the-art in food recommender systems and discuss research challenges related to the development of future food recommendation technologies.
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