Music recommending method and system

Abstract

The invention discloses a music recommending method and system. The music recommending method comprises steps as follows: music in a music library is analyzed, and music emotional characteristics are determined; the emotional state of a user is recognized, and user emotional characteristics are determined; the user emotional characteristics and the music emotional characteristics are matched, and a music recommendation list matched with the emotional state of the user is generated. According to the music recommending method and system, user emotion is analyzed, music of corresponding category is recommended with an emotional need matching method according to the emotional state of the user, precise, automatic and efficient music recommendation is realized, the recommendation content is more transcendent, and presetting by a user is not needed, therefore, the intelligent degree is higher, and the use feeling of the user is improved.

Description

technical field [0001] The invention relates to the technical field of data mining, in particular to a music recommendation method and system. Background technique [0002] With the continuous development and popularization of computer networks, people can obtain increasingly rich music resources conveniently and quickly. Therefore, people urgently need new technologies to manage music resources and realize effective retrieval and access to massive music resources. Traditional music retrieval is limited to the retrieval of music reference information such as music song name, singer name, lyricist, composer, etc., but such retrieval is far from satisfying people's retrieval and management of music from the perspective of music content. [0003] At present, music recommendations on music portals, Internet radio stations, and music playback software mostly use user playback history or user interaction input to analyze and classify user preferences, and select songs with similar...

AI Technical Summary

Problems solved by technology

Music emotion is a very important piece of information that characterizes music works. Accurate recognition of the emotion expressed in music can help people retrieve and access music that suits them more quickly. At present, there is no user emotion when recommending music to users. Status recommends suitable music, which has disadvantages in terms of diversification of recommendations, especially when the recommended music is quite different from the user's emotional state, which will affect the user's perception of the service

Images