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Real-time music recommendation method based on context pre-filtering

A recommendation method and contextual technology, applied in special data processing applications, instruments, electrical and digital data processing, etc., can solve the problem of inability to provide recommendation services, and achieve the effect of enhancing user loyalty and good music experience

Inactive Publication Date: 2014-02-05
ZHEJIANG UNIV
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, for many practical applications, the simple "user-item" binary relationship cannot provide efficient recommendation services

Method used

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  • Real-time music recommendation method based on context pre-filtering
  • Real-time music recommendation method based on context pre-filtering
  • Real-time music recommendation method based on context pre-filtering

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Embodiment Construction

[0029] With reference to accompanying drawing, further illustrate the present invention:

[0030] A real-time music recommendation method based on contextual pre-filtering, which is characterized in that after obtaining historical data of users using music services, the following operations are performed on current online active users:

[0031] 1) Extract the historical data of all users, build a "user-music-context" triple data model, and establish a personal record set P composed of music and context for each user u u ;

[0032] 2) For each current active user u a , based on its individual record collection Use the cosine correlation to evaluate the similarity between the context in the historical record and the current context c, and construct the K-nearest neighbor current context similar record set S(c);

[0033] 3) Use S(c) to transform the "user-music-context" ternary data model into a "user-music" binary data model;

[0034] 4) Use the collaborative filtering algo...

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Abstract

Disclosed is a real-time music recommendation method based on context pre-filtering. For each online active user, operations include firstly extracting historical data (such as the time, occasion and weather when the users listen to the music) of all users, constructing a 'user-music-context' ternary data model, and establishing an individual recording set formed by music and context for each user; secondly, constructing a current context similar record set of user K neighbors, and transferring the ternary data model into a binary model formed by the users and the music; finally, adopting a collaborative filtering based on fuzzy clustering algorithm to predict the degree of preference by the users to different music. The method has the advantages that context information is considered fully, and the music which is more consistent with users' preferences, current moods and surroundings can be recommended.

Description

technical field [0001] The invention relates to the technical field of music recommendation systems, in particular to the algorithm of the real-time music recommendation system based on contextual pre-filtering. Background technique [0002] Since the 1990s, with the rapid development of Internet technology, people have been immersed in the quagmire of information while obtaining rich information, making it difficult to efficiently collect the information they need, thus causing the problem of "information overload". At present, general-purpose search engines (such as Google, Baidu) are the most popular tools for obtaining information, but because of their versatility, such search engines cannot well satisfy the personalities of users with different backgrounds, different times, and different goals. Therefore, it is impossible to truly solve the problem of "information overload". Therefore, both academic circles and business circles put forward the concept of "personalized ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/637
Inventor 卜佳俊王学庆李平陈纯何占盈王灿吴晓凡
Owner ZHEJIANG UNIV
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