A song recommendation method, a song recommendation device, and a storage medium

By acquiring and integrating user listening behavior data and clustering information from music software, a target listening behavior vector is generated, which solves the problem of inaccurate song recommendation models for low-activity users and achieves song recommendations that are more in line with user preferences.

CN116541552BActive Publication Date: 2026-07-24TENCENT MUSIC ENTERTAINMENT TECH (SHENZHEN) CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-06-06
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Existing music software lacks sufficient samples of listening behavior from low-activity users when recommending songs, making it difficult for song recommendation models to accurately match user preferences.

Method used

By acquiring user listening behavior data in the target music module and clustering listening behavior in preset music modules, feature fusion is performed to generate a target listening behavior vector, and songs that match user preferences are recommended.

Benefits of technology

It improves the accuracy of song recommendations, making the recommended songs more in line with users' listening preferences.

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Abstract

The embodiment of the application discloses a song recommendation method, a song recommendation device and a storage medium, and is used in the technical field of information processing. The method comprises the following steps: obtaining target song listening behavior data of a user in a target music module and song listening behavior clustering corresponding to a preset music module; the amount of song listening behavior in the preset music module is greater than the amount of song listening behavior in the target music module, and the song listening behavior clustering is obtained by clustering the song listening behavior data in the preset music module; determining a target song listening behavior clustering corresponding to the target song listening behavior data in the song listening behavior clustering; performing feature fusion on a feature vector corresponding to the target song listening behavior data and a clustering vector corresponding to the target song listening behavior clustering, so as to obtain a target song listening behavior vector corresponding to the user; and recommending a song corresponding to the target song listening behavior vector to the user in the target music module, so that the song can be more in line with the preference of the user when the song is recommended to the user in the target music module.
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Citation Information

Patent Citations

  • Song recommendation method and apparatus

    CN106951527A

  • Heterogeneous graph song list multi-label recommendation method fusing node preference

    CN113268629A