Analysis of Music Retrieval Based on Emotional Tags Environment

Abstract

In general, tags are used to interpret the content of music, while the music itself expresses emotion. The emotional information conveyed by the same music is described by a large number of emotion tags in various ways. This paper proposes and establishes an algorithm for music retrieval based on emotional tags. By modelling user emotional tags and music, a bipartite graph with emotional tags and music as nodes is first created. The tags and semantic similarity between the music are then calculated using the T_SimRank algorithm, and the popularity of the music is calculated using the T_PageRank algorithm. Finally, the two methods are combined using the concept of ranking learning to produce the final ranking of the music. Experiments demonstrate that the method suggested in this paper can better satisfy user retrieval needs than conventional cosine similarity and tag co-occurrence-based similarity methods and that the fusion of multiple methods is preferable to a single method.