Video recommendation method and device, computer device and storage medium

A video recommendation and video technology, applied in the field of machine learning, can solve the problems of low video recommendation accuracy and loss of user feature information in the ACT model.

Active Publication Date: 2019-08-20
深圳市雅阅科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Embodiments of the present invention provide a video recommendation method, device, computer equipment, and storage medium, which can solve the problem that the ACT model loses information in user features and video features, resulting in low video recommendation accuracy

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  • Video recommendation method and device, computer device and storage medium
  • Video recommendation method and device, computer device and storage medium
  • Video recommendation method and device, computer device and storage medium

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Embodiment Construction

[0093] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below in conjunction with the accompanying drawings.

[0094] figure 1 It is a schematic diagram of an implementation environment of a video recommendation method provided by an embodiment of the present invention. See figure 1 At least one terminal 101 and server 102 may be included in the implementation environment.

[0095] The at least one terminal 101 is used to browse videos, and the server 102 is used to recommend videos to at least one user corresponding to the at least one terminal 101.

[0096] In some embodiments, an application client may be installed on each terminal of the at least one terminal 101, and the application client may be any client that can provide video browsing services, so that the server 102 can be based on the user's application The behavior log on the client collects ...

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PUM

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Abstract

The invention discloses a video recommendation method and device, a computer device and a storage medium, and belongs to the field of machine learning. The method comprises the steps of inputting a video into a first feature extraction network, performing feature extraction on at least one continuous video frame in the video, and outputting video features of the video; inputting the user data of the user into a second feature extraction network, performing feature extraction on the discrete user data, and outputting the user features of the user; performing feature fusion based on the video feature and the user feature to obtain a recommendation probability of recommending the video to the user; and determining whether to recommend the video to the user according to the recommendation probability. According to the method, for the user characteristics and the video characteristics, different networks are adopted for characteristic extraction, information in the user characteristics andthe video characteristics is prevented from being lost, and the video recommendation accuracy is improved.

Description

Technical field [0001] The invention relates to the field of machine learning, and in particular to a video recommendation method, device, computer equipment and storage medium. Background technique [0002] With the development of network technology, more and more users can watch videos at any time through the terminal. The server can recommend some videos that users may be interested in from the massive video database, so as to better satisfy users' video watching demand. [0003] In the recommendation process, the server can extract the joint features between any video in the video library and the user based on the Attentive Collaborative Filtering (ACT) model, and repeat the above steps for each video in the video library, and get more information. The multiple joint features corresponding to each video are further ranked according to the Euclidean distance between the multiple joint features, so that the video corresponding to the joint feature with the highest ranking is rec...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N21/25H04N21/45H04N21/466H04N21/482
CPCH04N21/251H04N21/252H04N21/4532H04N21/4826H04N21/4668H04N21/26603H04N21/25891H04N21/23418G06V20/41G06V10/454G06V10/82G06N3/08G06V10/806G06N3/045G06F18/253H04N21/44008H04N21/4666G06V20/46G06F18/251
Inventor 苏舟刘书凯孙振龙饶君丘志杰刘毅刘祺王良栋商甜甜梁铭霏陈磊张博
Owner 深圳市雅阅科技有限公司
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