A web-based application for semantic-driven food recommendation with reference prescriptions

Abstract

Food recommendation, as well as searching for health-related information, presents specific characteristics if compared with conventional recommender systems, since it often has educational purposes, to improve behavioural habits of users. In this paper, we discuss the application of Semantic Web technologies in a menu generation system, that uses a recipe dataset and annotations to recommend menus according to user’s preferences. Reference prescription schemes are defined to guide our system for suggesting suitable choices. The recommended menus are generated through three steps. First, relevant recipes are selected by content-based filtering, based on comparisons among features used to annotate both users’ profiles and recipes. Second, menus are generated using the selected recipes. Third, menus are ranked taking into account also prescription schemes. The system has been developed within a regional project, related to the main topics of the 2015 World Exposition (EXPO2015, Milan, Italy), where the University of Brescia aims at promoting healthy behavioural habits in nutrition.