Recipe suggestion for meal-sharing online Marketplaces

Meal-Sharing platforms, being part of the sharing economy, need strong user retention. Based on the principle that a recipe suggestion algorithm can help to increase user retention of such platform, this paper investigates the design of a recommender system for recipe suggestions. Different recommender system model are evaluated and compared using metrics such as meal sellability, RMSE, Recall and Precision. As no data is available of meal- sharing platform, this paper investigates on how to create a dataset that can be used by the recommender system. The comparaison of the models is done thanks a recommender system prototype.