Live video content pre-distribution method and electronic equipment

Abstract

The invention provides a live broadcast video content pre-distribution method and electronic equipment, and the method comprises the steps: obtaining an input feature corresponding to the live broadcast, predicting the corresponding pre-distribution opportunity according to the input feature corresponding to the live broadcast by using a deep neural network regression model trained by a training method of a model for predicting the pre-distribution opportunity of the live broadcast video; according to the method, the model for predicting the live pre-distribution opportunity is trained, the popularity feature of the anchor, the live broadcast feature of the anchor, the audience feature of the anchor and the arrival time difference feature of the audience during historical live broadcast of the anchor are used as input features, and the arrival time difference of the audience when the corresponding live broadcast event occurs is indicated as a label; and training the deep neural network regression model to enable the model to adapt to the pre-distribution opportunities adapted to the corresponding features for different anchors for the features corresponding to the anchors, thereby reducing the influence of too late pre-distribution on the user experience.

Description

technical field [0001] The present invention relates to the field of mobile Internet, in particular to the field of live video data storage, and more specifically, to a method for pre-distributing content of live video and an electronic device. Background technique [0002] With the advent of the mobile Internet era, the number of netizens is increasing year by year, the coverage of mobile smart devices (such as smartphones, tablets, smart glasses, etc.) is getting higher and higher, and the proportion of 4G+Wi-Fi in the mobile Internet is also increasing. High, the mobile media business is currently in a stage of rapid development. Inheriting the advantages of the mobile Internet, live video broadcasting (webcasting, referred to as live broadcasting) has the characteristics of intuition, speed, real-time, good form of expression, and strong interactivity. It has become a representative of mobile media, showing an explosive development model. As one of the most popular mobi...

AI Technical Summary

Problems solved by technology

[0006] However, the inventor found through research that the key factor affecting the viewer's QoE is to reduce the start-up delay (Startup Delay) between the viewer's click to play and the start of the first frame. QoE

If the video live broadcast data is pre-distributed to all edge servers, it can effectively reduce the startup delay, but it will cause unnecessary waste and challenges to network resources and storage resources.

If a unified pre-distribution strategy is adopted for all anchors, it will also face the problems of waste of resources and difficult coordination of QoE

[0007] At present, there is a lack of research on pre-distribution strategies for live broadcasts, and it is necessary to design pre-distribution technologies according to the characteristics of live video broadcasts.

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