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Method and device for recommending audio and video
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A recommendation method, audio and video technology, applied in the multimedia field, can solve the problems of not considering the differences of different users, and the inability to recommend users, so as to achieve accurate audio and video recommendations and achieve personalized effects
Active Publication Date: 2020-03-13
MIGU MUSIC CO LTD
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[0003] However, the rankings are usually ranked according to the comprehensive scores of all users, or according to the total downloads. This music recommendation method does not consider the differences between different users, so it cannot accurately recommend users.
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Embodiment 1
[0044] This embodiment takes the server side as an example to describe the implementation process of the audio and video recommendation method in detail. Such as figure 1 As shown, the implementation process of the audio and video recommendation method in this embodiment includes the following steps:
[0045] Step 101: Obtain the user's scene according to the user's login method, the user's environment information, and the user's operation behavior.
[0046] Specifically, the server superimposes a user's login method, the environment information of more than one user, and at least one user operation behavior to determine the user's scene;
[0047] Or superimpose the relationship between a user's login method and the environment information of more than one user to determine the user's scene;
[0048] Or superimpose a user login method and at least one user operation behavior to determine the user's scene.
[0049] Here, the relationship superposition can be performed in the...
Embodiment 2
[0092] In order to implement the method in Embodiment 1, this embodiment provides a server, such as figure 2 As shown, the server includes: an acquisition module 21, a quantization module 22, and a generation module 23; wherein,
[0093] An acquisition module 21, configured to acquire the user's scene according to the user's login method, the user's environment information, and the user's operation behavior;
[0094] The quantification module 22 is configured to respectively quantify the user login method, user environment information, and user operation behavior to obtain quantified scenarios.
[0095] The generating module 23 is configured to generate an audio and video recommendation table matching the quantized scene and make recommendations.
[0096] The acquisition module 21 is specifically used to superimpose a user's login method, the environment information of more than one user, and at least one user operation behavior to determine the user's scene; The informatio...
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Abstract
The invention discloses an audio and video recommending method comprising the following steps: obtaining a user scene according to a user logging mode, a user located environment, and user operation behaviors; respectively quantifying the user logging mode, the user located environment, and the user operation behaviors, thus obtaining a quantified scene; forming an audio and video recommend list matched with the quantified scene, and recommending the audio and video recommend list. The invention also discloses a server.
Description
technical field [0001] The present invention relates to the field of multimedia technologies, in particular to an audio and video recommendation method and device. Background technique [0002] At present, music websites and music software generally recommend music to users through music rankings. For example, music software recommends to users the music with the highest user rating or the most downloaded music in the recent period. [0003] However, the rankings are usually ranked according to the comprehensive scores of all users, or according to the total number of downloads. This music recommendation method does not consider the differences between different users, so it cannot accurately recommend users. Contents of the invention [0004] In view of this, the embodiments of the present invention expect to provide an audio and video recommendation method and device, which can realize accurate recommendations for different users. [0005] In order to achieve the above ...
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