Research on Personalized Song Recommendation System Based on Vocal Music Feature Data Mining

Authors

  • Su Ma

Abstract

Before the recommendation system appeared, search engine was the main method to solve the problem of information overload. However, when users' needs are not clear, or users can't clearly explain their own information needs, search engines will be weak. The recommendation system does not need users to provide clear requirements. It builds a model for users' interests by collecting users' historical behaviors and combining other related information, so as to find out the items that users may like and recommend them to users. Music recommendation system mainly collects the behaviors and interests of existing users, finds similar behavior habits and hobby user groups, analyzes the behaviors and interests of interest groups, and realizes personalized recommendation services by using scoring methods. This paper proposes a personalized song recommendation method based on vocal music feature data mining. According to the user's listening records, it generates a listening preference model for the user, and then calculates the similarity between the user and the song, and then recommends the song with the closest preference for the user.

Published

2020-12-01

Issue

Section

Articles