Short video personalized recommendation method and system based on multi-modal graph convolutional network

A technology of convolutional network and recommendation method, which is applied in the field of short video personalized recommendation based on multimodal graph convolutional network, can solve the problem of ineffective and poor accuracy of short video personalized recommendation, inability to express multimodal content information, and user Preference expression deviation and other issues to achieve the effect of improving accuracy and comprehensibility, accurate and effective personalized recommendation
CN110337016AActive Publication Date: 2019-10-15SHANDONG UNIV
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Patent Information

Authority / Receiving Office
CN ยท China
Current Assignee / Owner
SHANDONG UNIV
Publication Date
2019-10-15

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Abstract

The invention provides a short video personalized recommendation method and system based on a multi-modal graph convolutional network. The short video personalized recommendation method based on the multi-modal graph convolutional network comprises the following steps: respectively constructing user-short video graph structure based on an image mode, an audio mode and a text mode of a short video;wherein points in the short video graph structure represent a user and a short video, and a connection line between the points represents interaction between the user and the short video; inputting the user-short video graph structure into a corresponding graph convolutional neural network, respectively calculating a user and a short video for expressing each mode through a polymerization layer of the corresponding graph convolutional neural network, and combining expressions of each mode of the user and the short video by utilizing a fusion layer of the corresponding graph convolutional neural network to obtain final expressions of the user and the short video; and using a Bayesian personalized sorting algorithm to sequentially recommend paired sequences of final expressions of the userand the short video.
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Description

technical field

[0001] The disclosure belongs to the field of short video personalized recommendation, and in particular relates to a short video personalized recommendation method and system based on a multi-modal graph convolutional network. Background technique

[0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art.

[0003] Personalized recommendations have become a core component of many online content sharing services, especially short video platforms. Various short video applications, such as Vine, Instagram, Kuaishou, Douyin, Meipai, WeChat, Weibo, Tencent Weishi, etc., have developed rapidly in recent years. The short video is seamlessly connected to various social platforms on the Internet, so that it can be directly shared on social networks after shooting. Short video combines multiple modes of text, audio, and image, which can meet users' expression and communi...

Claims

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