Video recommendation method and device, storage medium and computer equipment

A video recommendation and video technology, applied in the fields of computer equipment, devices and storage media, and video recommendation methods, can solve the problems of not being able to get popular video recommendations, consuming computing time, and repeating data calculations.

Active Publication Date: 2020-07-07
BIGO TECH PTE LTD
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

However, when the amount of data is large, this solution will consume a lot of calculation time because the calculated behavior data will be recalculated, resulting in a large amount of calculation time, so that the final calculated popular video has been in the past for a while popular videos, at the same time, new popular videos cannot be exposed more quickly, and real-time popular video recommendations cannot be obtained

Method used

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

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specific Embodiment

[0094] First, the system acquires the behavior data within that time interval every other time interval. According to the Bayesian score formula above, it is aggregated to calculate a basic information combination (action_score, action_time, dispatch_times, post_time) for each video. Among them, action_score is the basic score, that is, the behavior score of the target video; action_time is the behavior time of the target video, that is, the end time of the time interval, which is normalized to a time point in the time interval; dispatch_times is the number of behaviors, namely The sum of all behavior times in the time interval; post_time is the time when the video was uploaded, that is, the time when the video was released. Stored in the cache, marked with action_time, as an intermediate result.

[0095] Then, all stored intermediate results in a sliding window are obtained, and a certain time decay is performed on the basic score of each video in different time intervals rel...

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Abstract

The invention provides a video recommendation method and device, a storage medium and computer equipment. The method comprises: obtaining behavior data of a target video at each time interval in a preset time period; according to the behavior data, obtaining time interval end time, video release time and video behavior times of the target video in each time interval, and a behavior score of the user for the target video; calculating to obtain a recommendation score of the target video according to the time interval end time, the video publishing time and the video behavior frequency of the target video in each time interval in the preset time period and the behavior score of the user for the target video; and recommending the video according to the recommendation score of the target video.According to the method, the data operation time during video recommendation is shortened, new popular videos can be obtained more quickly, and the video recommendation effect is optimized.

Description

technical field [0001] The present invention relates to the technical field of video data processing, in particular, the present invention relates to a video recommendation method, device, storage medium, and computer equipment. Background technique [0002] The recommendation system needs to predict the user's future behavior and interest based on the user's historical behavior and interest, and recommend items to the user that meet the user's expectations. When new users come in, due to the lack of historical data, personalized recommendations cannot be made. This is the user cold start problem of item recommendation. Under normal circumstances, for the problem of user cold start, the hot recommendation method is mainly used, that is, to recommend items that the current user group prefers to the user, and then perform personalized recommendation after the user data is sufficient. [0003] In the popular recommendation, the commonly used method is to calculate the populari...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N21/466H04N21/25
CPCH04N21/4668H04N21/4667H04N21/4663H04N21/251
Inventor 张航金子刚黎猛
Owner BIGO TECH PTE LTD
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