Music recommendation algorithm based on content and user history

Abstract

The invention provides a music recommendation algorithm based on content and user history, belonging to multimedia analysis technology field. The recommendation algorithm comprises: using a piece of music which is appointed by the user as interested music as input of the recommendation algorithm, calculating recommendation probability u (i, j) of other music relative to the user input by utilizing a recommendation algorithm based on cooperation to analysis user history, wherein the user history is music appreciated by the user in the past; calculating similarity s (i, j) between each piece of music and the user input music by utilizing a spatial distance relation of characteristics according to three music characteristics; calculating importance g (i, j) of other pieces of music relative to the user input music by utilizing characteristic vector centrality in a graph based analysis method to analysis music network;determining weight relationship among the recommendation algorithm based on cooperation, similarity analysis algorithm and analysis algorithm based on characteristic vector centrality; and calculating final recommendation probability of each piece of music by fusing the three algorithms. The music recommendation algorithm provided in the invention saves time and energy of users and solves appreciation preference problem of users.

Description

technical field [0001] The invention relates to a music recommendation algorithm based on content and user history, and belongs to the technical field of multimedia analysis. Background technique [0002] Currently, music analysis and recommendation algorithms mainly include tag-based methods, content-based methods, machine learning-based methods, and emotion-based methods. However, these methods only analyze objective factors, without considering subjective factors such as user behavior and habits, and the generated recommendation results cannot meet the needs of different users. Although the emotion-based method maps music and human emotions, it still cannot reflect the individual differences of users due to the limited information of emotional expression. Contents of the invention [0003] Aiming at the deficiencies of the prior art, the present invention provides a music recommendation algorithm based on content and user history. [0004] The invention analyzes the m...

AI Technical Summary

Problems solved by technology

[0004] The invention analyzes music from both subjective and objective aspects, overcomes the deficiencies in existing music analysis and recommendation algorithms, and solves the problem of user appreciation preference

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