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A method, device, terminal and storage medium for similarity correction between live broadcast rooms

A technology of live broadcasting and similarity, applied in the computer field, can solve the problem of low reliability of similarity, achieve the effect of overcoming low reliability and improving reliability

Active Publication Date: 2021-03-16
WUHAN DOUYU NETWORK TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, among the many big data algorithm solutions recommended by live broadcast rooms, a simple and feasible solution is to recommend live broadcast rooms similar to the historical live broadcast rooms that target users have watched recently. Usually, offline data can be used to calculate the difference between two live broadcast rooms. The similarity between two live broadcast rooms is used to determine the live broadcast room similar to the historical live broadcast room. The existing methods for calculating the similarity between two live broadcast rooms usually have the problem of low reliability of the calculated similarity.

Method used

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  • A method, device, terminal and storage medium for similarity correction between live broadcast rooms
  • A method, device, terminal and storage medium for similarity correction between live broadcast rooms
  • A method, device, terminal and storage medium for similarity correction between live broadcast rooms

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Embodiment 1

[0024] The method for modifying the similarity between live broadcast rooms provided in this embodiment is applicable to the calculation of the similarity between two live broadcast rooms based on live broadcast room recommendation. The method can be performed by a device for correcting similarity between live broadcasts, which can be implemented by software and / or hardware, and which can be integrated in a device with computing and network functions, such as a typical user terminal device, such as a server , tablet or desktop computer, etc. see figure 1 , the method of this implementation specifically includes the following steps:

[0025] S110. Calculate the offline similarity between the first live broadcast room and the second live broadcast room by using the offline data within a preset time period.

[0026] Wherein, the preset time period can be the historical time period of the nearest day, week or month, etc. from the current time, and the offline data can be the his...

Embodiment 2

[0063] figure 2 It is a schematic structural diagram of a device for correcting similarity between live broadcasts provided by Embodiment 2 of the present invention. see figure 2 , the device for correcting the similarity between live broadcasts in this embodiment includes:

[0064] The offline similarity calculation module 210 is used to calculate the offline similarity between the first live room and the second live room by using offline data within a preset time period;

[0065] The correction parameter determination module 220 is used to determine the real-time co-occurrence times of the co-occurrence situations between the first live room and the second live room, the number of first user behaviors corresponding to the first live room, and the second The number of second user behaviors corresponding to the live broadcast room;

[0066] The offline similarity modification module 230 is configured to modify the offline similarity by using the real-time co-occurrence ti...

Embodiment 3

[0087] image 3 A schematic structural diagram of a similarity correction terminal between live broadcasts provided by Embodiment 3 of the present invention. image 3 A block diagram of an exemplary similarity modification terminal 312 between live broadcasts suitable for implementing embodiments of the present invention is shown. image 3 The displayed similarity correction terminal 312 between live broadcasts is only an example, and should not limit the functions and scope of use of this embodiment of the present invention.

[0088] Such as image 3 As shown, the similarity correction terminal 312 between live broadcasts is represented in the form of a general-purpose computing device. The components of the similarity correction terminal 312 between live broadcasts may include but are not limited to: one or more processors 316, memory 328, connected to different system components (including memory 328 and processor 316) bus 318.

[0089] Bus 318 represents one or more of ...

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Abstract

The embodiment of the invention discloses a method, a device, equipment and a storage medium for correcting similarity between live broadcasts. The method comprises the following steps: using the offline data in a preset time period to calculate the offline similarity between the first live broadcast and the second live broadcast; determining a real-time co-occurrence number with co-occurrence between the first live broadcast room and the second live broadcast room, a first user behavior number corresponding to the first live broadcast room and a second user behavior number corresponding to the second live broadcast room according to the real-time data corresponding to the current time. The offline similarity is corrected by using the real-time co-occurrence times, the first user behaviortimes and the second user behavior times. The embodiment of the invention overcomes the problem of low reliability of similarity between two pairs of live broadcasts calculated by using offline data in the prior art, and improves the reliability of similarity calculation between two pairs of live broadcasts.

Description

technical field [0001] Embodiments of the present invention relate to computer technology, and in particular to a method, device, terminal and storage medium for similarity correction between live broadcasts. Background technique [0002] In the application field of big data, an important direction is to make personalized recommendations to users based on massive data. For the Internet live broadcast platform, the personalized recommendation is to accurately recommend the live broadcast room that the current user is interested in. [0003] At present, among the many big data algorithm solutions recommended by live broadcast rooms, a simple and feasible solution is to recommend live broadcast rooms similar to the historical live broadcast rooms that target users have watched recently. Usually, offline data can be used to calculate the difference between two live broadcast rooms. The similarity between two live broadcast rooms is determined by the similarity of the historical...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N21/442H04N21/466
CPCH04N21/44213H04N21/4668
Inventor 王璐
Owner WUHAN DOUYU NETWORK TECH CO LTD