Multimedia content evaluation method and device and training method thereof

A multimedia content and training method technology, applied in the field of multimedia content processing, can solve problems such as prolonging user retention and attracting new users, lack of high-quality content recommended by new users, and failure to effectively push high-quality content, so as to improve the performance of evaluation tasks, The effect of difficult data acquisition and large subjective influence factors

Pending Publication Date: 2021-01-05
TENCENT MUSIC ENTERTAINMENT TECH SHENZHEN CO LTD
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Problems solved by technology

However, there is a lack of effective means to recommend high-quality content to new users who lack behavioral data
Interest-based recommendations may also cause some newly

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  • Multimedia content evaluation method and device and training method thereof
  • Multimedia content evaluation method and device and training method thereof
  • Multimedia content evaluation method and device and training method thereof

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[0056] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in combination with specific implementation methods and accompanying drawings. Here, the exemplary embodiments and descriptions of the present invention are used to explain the present invention, but not to limit the present invention.

[0057] In the embodiment of the present invention, "network" has a conventional meaning in the field of machine learning, such as neural network (NN), deep neural network (DNN), convolutional neural network (CNN), recurrent neural network (RNN), other Machine learning or deep learning networks or combinations or modifications thereof.

[0058] In the embodiment of the present invention, "model" has a conventional meaning in the field of machine learning, for example, the model may be a machine learning or deep learning model, for example, a machine learning or deep learning mode...

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Abstract

The invention discloses a training method of a multimedia content evaluation model, and the evaluation model comprises an evaluation network module and a post-processing unit; the evaluation network module comprises a classification network sub-module and a subsequent dimension reduction sub-module, and the training method comprises the following steps: training the evaluation network module; inputting the plurality of picture data into the trained evaluation network module to obtain evaluation network module output, and inputting the evaluation network module output into a post-processing unit for processing to determine post-processing parameters for converting the evaluation network module output into a final evaluation value. The invention also provides a multimedia content evaluationmethod and evaluation device, and electronic equipment. According to the scheme, the training data acquisition difficulty can be effectively reduced, learning of multimedia content features is betterdriven, and therefore the automation degree, efficiency and accuracy of multimedia content evaluation are improved.

Description

technical field [0001] The present application relates to the technical field of multimedia content processing, in particular to a multimedia content evaluation method and device. The present application also relates to a training method for a multimedia content evaluation model. In addition, the present application also relates to related electronic equipment. Background technique [0002] Currently, multimedia content including User Generated Content (UGC), such as music, short videos or videos, is generated in large quantities and widely disseminated. [0003] However, a large amount of multimedia content, especially user-generated content, is uneven, which hinders better and faster mining of high-quality content. [0004] For example, in terms of multimedia content, such as short video review, the number of daily short video platforms has reached 100,000. If a purely manual audit is used, it will not only take a long time but also cost a lot of labor. For a large num...

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Application Information

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IPC IPC(8): G06Q10/06G06K9/62G06N3/04G06N3/08G06F16/45G06F16/48G06F17/18
CPCG06Q10/0639G06N3/084G06F16/45G06F16/48G06F17/18G06N3/045G06F18/2414G06F18/214
Inventor 关文婕吴斌雷兆恒
Owner TENCENT MUSIC ENTERTAINMENT TECH SHENZHEN CO LTD
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