Music Recommendation System Using Machine Learning

EasyChair Preprint no. 12850

Abstract

Music recommendation system is like musical friend that understands listeners preferences and Suggests songs and playlists to the listeners. Music

recommendation based on past data suggests songs to the listeners according to the listeners choice. However, customers often face challenges in selecting the

most suitable song from such an extensive music collection. Various methods exist for developing song recommendation systems, including collaborative

filtering, content-based filtering, and hybrid method. Initially, the system collects large amount of user data, including listening history and ratings to create a

detailed profile. To construct a music recommendation system, we can use different machine learning algorithms, such as cosine similarity, K-nearest neighbor,

Weighted Product Method. Hybrid System with Singular Value Decomposition, Factorization Machine will be used.

Keyphrases: collaborative filtering, content-based filtering, machine learning

@Booklet{EasyChair:12850,
  author = {Leela Krishna Reddy and Hansa Vaghela},
  title = {Music Recommendation System Using Machine Learning},
  howpublished = {EasyChair Preprint no. 12850},

  year = {EasyChair, 2024}}