Video recommendation method, system and device and storage medium

Abstract

The invention discloses a video recommendation method, system and device and a storage medium, and the method comprises the steps: obtaining a first user structure diagram of a first video user, and carrying out the traversal processing of the first user structure diagram through a diagram traversal algorithm, and obtaining a first feature set of the first video user; obtaining a first video structure chart of the first video user, and traversing the first video structure chart through a chart traversal algorithm to obtain a second feature set of the first video user; determining the correlation degree between the features in the first feature set and the second feature set; and determining supervision data according to the correlation degree, determining a training sample according to the first feature set and the second feature set, inputting the supervision data and the training sample into a pre-constructed neural network model to obtain a trained video recommendation model, and determining a video recommendation result according to the video recommendation model. According to the method, the video recommendation result better fits the preference of the user, the user experience is improved, and the method can be widely applied to the technical field of video recommendation.

Description

technical field [0001] The present invention relates to the technical field of video recommendation, in particular to a video recommendation method, system, device and storage medium. Background technique [0002] Short video is a short video, which is a method of Internet content dissemination. Generally, it refers to videos that are disseminated on new Internet media with a duration of less than 30 minutes. With the popularization of mobile terminals and the speeding up of the Internet, the short, smooth and large-flow dissemination of content has gradually gained the favor of major platforms, fans and capital. [0003] In the prior art, in the process of short video recommendation, there are problems that the recommendation ability is not comprehensive enough, and the short video recommendation based on user closeness and user attribute characteristics as the main feature is not enough, so that the result of the video recommendation cannot accurately fit the user. prefer...

AI Technical Summary

Problems solved by technology

[0003] In the prior art, in the process of short video recommendation, the recommendation ability is not comprehensive enough, and short video recommendation based on user closeness and user attribute characteristics as the main features is lacking. As a result, the results of video recommendation cannot accurately fit the user's preferences, which affects the user's experience

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