Towards a Knowledge-aware Food Recommender System Exploiting Holistic User Models
Cataldo Musto, Christoph Trattner, Alain D. Starke, Giovanni Semeraro
Abstract
Food recommender systems typically rely on popularity, as well as similarity between recipes to generate personalized suggestions. However, this leaves little room for users to explore new preferences, such as to adopt healthier eating habits.
Topics & Concepts
Recommender systemPopularityComputer scienceSimilarity (geometry)World Wide WebInternet privacyArtificial intelligencePsychologySocial psychologyImage (mathematics)Recommender Systems and TechniquesAdvanced Text Analysis TechniquesNutritional Studies and Diet