Music Recommendation System Based on Machine Learning

Abstract

Machine learning is a hot topic of research in recent years and has a very wide range of applications in the fields of banking, insurance, transportation, biology, and medicine. A recommendation system is an information filtering system that uses algorithms to pinpoint a user's biased preferences by filtering redundant information from a large dataset and recommending new relevant content to the target user that he or she may like. In this paper, we categorize and outline several mainstream music recommendation methods: content-based and collaborative filtering recommendations, as well as weighted hybrid models of both.