Personalized music recommendation method and system

A recommendation method and music technology, applied in special data processing applications, instruments, electrical and digital data processing, etc., can solve problems such as slow and irregular changes, adjustment of recommended content, noise recommended data, etc., to achieve the effect of improving accuracy

Inactive Publication Date: 2012-09-05
北京多米在线科技股份有限公司
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Problems solved by technology

[0005] The problem with the above-mentioned existing technologies is that the user’s taste usually changes with time, not only with slow and non-periodic changes over a long time span, but also according to short time spans such as days and weeks and application scenarios. cyclical changes
If it is only mechanically identified that the user has tastes for country music and RAP music, w

Method used

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  • Personalized music recommendation method and system
  • Personalized music recommendation method and system
  • Personalized music recommendation method and system

Examples

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Example Embodiment

[0030] The following describes the implementation process of the present invention in detail through specific embodiments.

[0031] The present invention is used to obtain user tastes, especially user tastes associated with time. At the same time, according to the acquired tastes of the users, songs that meet the tastes of the users are recommended for the users.

[0032] Such as Figure 1A Shown is a schematic diagram of the structure of the personalized music recommendation system of the present invention. At least one user terminal 1 is connected to the music recommendation server 2 through the network. The music recommendation server 2 includes a user data storage management module 21, a similarity calculation module 22, a user taste discovery module 23, and a recommendation filtering module 24. The user terminal 1 includes a PC, a mobile phone, a PDA, a tablet computer, a vehicle-mounted mobile terminal, and the like.

[0033] The user terminal 1 logs in to the music recommend...

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Abstract

The invention discloses a personalized music recommendation method and system. The method comprises the following steps of: 1, generating user behavior data by a music recommendation server according to the operation of a user terminal on songs, wherein the user behavior data includes an operation time label, an operation frequency label and a song label; 2, performing clustering calculation of the user behavior data to obtain multiple result labels; 3, weighting the operation frequencies of the user behavior data according to the time interval thereof, wherein the weight is higher when the time interval is closer to the current moment; 4, normalizing the user behavior data after the weighting; 5, performing permutation and combination of the multiple result labels, calculating the similarity between the normalized user behavior data and each permutation and combination sequentially, obtaining the user taste according to the calculation result, and selecting a user taste model from the user taste; and 6, recommending songs to the user terminal by the music recommendation server according to the user taste model.

Description

Technical field [0001] The invention relates to a music data processing service, in particular to a personalized music recommendation method and system. Background technique [0002] Users usually use two ways when listening to songs, one is to use a traditional audio player to play locally, and the other is to search or audition online through the Internet. Traditional audio players can only play music files that users already have, and cannot expand the user's listening range, and cannot help users discover other songs based on their hobbies. The way of online search and audition through the network solves the problem of expanding the user's listening range. In the prior art, it is also possible to recommend songs for users based on the network. Recommendations are generally implemented in two ways: generating recommendations based on selection consistency and generating recommendations based on collaborative filtering. [0003] Taking selection consistency as an example, the ...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 赵凌孙武石建平奉佑生
Owner 北京多米在线科技股份有限公司
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