Collaborative Filtering based Hybrid Music Recommendation System
Jagendra Pratap Singh · 2020
Even though people are nowadays listening all types of songs, still algorithms are struggling in many fields. With less historic figures, how does the system know the listeners like a new artist or a new song? And, how do you know which songs to suggest to new users? In this perspective, the proposed research work aims to assess the likelihood that a user will listen to the song repeatedly after the first apparent listening experience begins in the time frame. If the user has a recurring auditory occurrence within a month following the first apparent listening event, its goal is 1 and otherwise 0 identified. The approaches like collaborative filtering, content-based filtering, singular value decomposition (SVD) and factorization machines (FM) are also used. At last, the proposed system is hybridized by using SVD and FM.