Heterogeneous Information Network-based Music Recommendation System Using Deep Learning

Abstract

The proposed system aims to enhance an existing music recommendation system using Heterogeneous Information Networks (HINs) and Graph Neural Networks (GNNs). It introduces a deep learning model to improve accuracy and performance. The framework captures diverse information, such as artist, song, genre details, user preferences, and listening history. The paper outlines a step-by-step methodology for incorporating HINs and GNNs in the recommendation process.