UIFRS-HAN: User interests-aware food recommender system based on the heterogeneous attention network

Saman Forouzandeh, Kamal Berahmand, Mehrdad Rostami, Aliyeh Aminzadeh, Mourad Oussalah

Abstract: Highlights•A novel food recommender system based on a heterogeneous attention network.•The dual attention method is used to learn the meta-path in HIN.•Employing unsupervised learning based on hierarchical attention in the HIN.•The experiment method involves two real datasets based on heterogeneous graphs.