Internet children video like PK management system and method
By designing a children's video likes PK management system, the problems of inaccurate video quality assessment and data risks in traditional methods are solved, the fairness of video quality assessment and data security are achieved, and the user experience and platform reputation are improved.
Patent Information
- Application Number
- CN202510595676.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-09
- Publication Date
- 2025-09-19
AI Technical Summary
The traditional method of competing for likes on children's videos lacks systematicity and scientificity, making it difficult to accurately evaluate video quality. It also involves data risks and like-boosting behaviors, which affect fair competition and user experience.
An Internet children's video likes PK management system is designed, which includes a children's video likes data statistics module, a PK object matching module, a likes data risk analysis module and a console management output module. Through data analysis, risk assessment and early warning mechanisms, it manages the entry of videos into the video pool, matches PK objects and monitors the changes in likes data.
The whole process of children's video likes competition has been managed to ensure the fairness of video quality assessment and data security, prevent the behavior of brushing likes, and improve user experience and platform reputation.
Smart Images
Figure CN120672364A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of big data management, and more specifically to an Internet children's video likes PK management system and method. Background Art
[0002] With the vigorous development of Internet social networks, the like function has become an indispensable part of many websites and applications. This function not only allows users to more intuitively understand how many people recognize their videos, articles and other content, but also greatly enhances the user's interactive experience. At the same time, children's video content is becoming increasingly abundant on Internet platforms, attracting a large number of users' attention and participation. In order to improve user experience and increase user stickiness, many platforms have introduced children's video like PK functions, which stimulate users' enthusiasm for participation and competitive awareness by comparing the number of likes received by different videos.
[0003] However, the traditional method of competing for likes on children's videos often lacks systematicity and scientificity. The lack of in-depth data analysis makes it difficult to accurately evaluate the quality of the videos. There are also problems such as data risks. The number of likes is an important indicator for measuring video quality, but some users or video producers may resort to methods such as brushing to increase the number of likes. This behavior not only destroys the environment of fair competition, but may also have a negative impact on the platform's reputation and user experience. Summary of the Invention
[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides an Internet children's video likes PK management system to solve the problems existing in the above-mentioned background technology.
[0005] The present invention provides the following technical solution: an Internet children's video likes PK management system, comprising: a children's video likes data statistics module, a children's video PK object matching module, a likes data risk analysis module, a likes data risk warning module, and a console management output module; The children's video likes data statistics module includes a video review unit, a video data collection unit and a video quality assessment unit. The module analyzes the video data to evaluate whether the video has entered the video pool and transmits the evaluation result to the children's video PK object matching module; The children's video PK object matching module receives the evaluation results transmitted by the children's video likes data statistics module, performs PK object matching on the videos in the video pool and monitors the changes in the PK object likes data in real time; The likes data risk analysis module includes a first unit and a second unit. The first unit performs a first risk analysis on the video data in the children's video likes data statistics module, and the second unit performs a second risk analysis on the likes data monitored by the children's video PK object matching module, and transmits the analysis results to the likes data risk warning module; The likes data risk warning module sends warning information to the console management output module based on the first risk analysis result and the second risk analysis result of the likes data risk analysis module; The console management output module receives the warning information sent by the likes data risk warning module, and sends control instructions through the console to complete the management of the children's video likes PK.
[0006] Preferably, in the children's video likes data statistics module, the video review unit is responsible for reviewing the uploaded children's videos and publishing the videos after passing the review standards. The video data collection unit is responsible for collecting data on the videos and transmitting the collected likes data to the video quality assessment unit to assess the quality of the videos.
[0007] Preferably, the video quality assessment unit assesses the video quality as follows: Step S1: Set the video data collection deadline. The time period from the video release to the video data collection deadline is the first stage. Divide the first stage of the video to be evaluated into n sub-time periods, where i=1, 2, 3, ..., n, and i represents the number of each sub-video in the first stage; Step S2: Collect the number of likes received in each sub-time period in the first stage of the video to be evaluated, and sum the number of likes received to obtain the total number of likes received in the first stage of the video to be evaluated. The calculation formula is: ,in Indicates the total number of likes received by the video to be evaluated in the first stage. Indicates the number of likes received in each sub-time period in the first stage of the video to be evaluated; Step S3: The total number of likes received in the first phase of the video to be evaluated obtained in step S2 and the preset threshold of likes For comparison, if the total number of likes received in the first stage of the video to be evaluated is Greater than or equal to the preset threshold of likes , the video quality is evaluated by the video quality evaluation unit; otherwise, the video to be evaluated does not enter the video quality evaluation unit; Step S4: The video quality assessment unit receives the video to be assessed transmitted in step S3 and performs quality assessment on the video. The calculation formula is: ,in Indicates the quality evaluation value of the video to be evaluated. Indicates the quality impact factor of the video to be evaluated, represents a constant, Indicates the average number of likes received in each sub-time period in the first stage of the video to be evaluated; Step S5: The quality evaluation value of the video to be evaluated The threshold for entering the video pool For comparison, if the quality evaluation value of the video to be evaluated is Less than or equal to the threshold for entering the video pool , the video to be evaluated will be put into the video pool, otherwise, the video to be evaluated will not be put into the video pool.
[0008] Preferably, in the children's video PK object matching module, the specific content of PK object matching of videos in the video pool is as follows: Arrange the m videos in the video pool in sequence according to the time when the videos enter the video pool to form an initial video pool sequence, where m≥2. When m<2, no video pool is formed. The second phase of likes statistics is performed on the m videos in the initial video pool. The second phase represents the time period from the video data collection deadline set by the video quality assessment unit to the time when the video enters the video pool to form the initial video pool sequence. The likes distribution coefficient of each video in the initial video pool is calculated using the following formula: ,in Represents the likes distribution coefficient of each video in the initial video pool, represents the impact factor of the number of likes, Indicates the total number of likes received by each video in the initial video pool in the first stage. Indicates the total number of likes received by each video in the initial video pool in the second phase. Indicates the statistical time of the first stage of each video in the initial video pool. Indicates the statistical time of the second stage of each video in the initial video pool. Indicates the playback duration of each video in the initial video pool. Indicates the preset number of likes corresponding to the playback time of each video in the initial video pool; According to the likes distribution coefficient of each video in the initial video pool, each video is arranged in descending order to form a reorganized video pool sequence. Adjacent videos are extracted according to the adjacent video PK principle to generate PK video matching pairs, and the changes in the likes data of the PK objects are monitored in real time.
[0009] Preferably, in the likes data risk warning module, the first unit performs a first risk analysis on the video data in the children's video likes data statistics module to calculate a first risk coefficient of the first stage of the video to be evaluated; The second unit performs a second risk analysis on the likes data monitored by the children's video PK object matching module and calculates a second risk coefficient.
[0010] Preferably, the first risk coefficient of the first stage of the video to be evaluated is calculated using the following formula: ,in represents the first risk coefficient of the first stage of the video to be evaluated, n represents the number of sub-time periods divided into the first stage of the video to be evaluated, Indicates the number of likes received in each sub-time period in the first stage of the video to be evaluated; The first risk factor of the first stage of the video to be evaluated Compared with the preset risk factor threshold range, if the first risk factor of the first stage of the video to be evaluated is If the data is within the preset risk factor threshold, it is judged to be risk-free; otherwise, it is judged to be risky.
[0011] Preferably, the specific content of calculating the second risk coefficient is as follows: Divide the videos in the video pool into n sub-time periods, where i = 1, 2, 3, ..., n, and i represents the number of each sub-video; Analyze the growth rate of likes data for each sub-video, and calculate the second risk coefficient of the videos in the video pool based on the growth rate of likes data for each sub-video. The calculation formula is: ,in Indicates the second risk factor of the videos in the video pool, Indicates the growth rate of likes data for each sub-video, represents the maximum growth rate of likes data of each sub-video, e represents a constant, Indicates the stability coefficient of the video in the video pool; The second risk factor of the video in the video pool Compare with the preset risk factor threshold range, if the second risk factor of the video in the video pool is If the data is within the preset risk factor threshold, it is judged to be risk-free; otherwise, it is judged to be risky.
[0012] Preferably, in the likes data risk warning module, based on the first risk analysis result and the second risk analysis result of the likes data risk analysis module, when the first risk analysis result is risky, the video will not enter the video pool, and a warning message will be sent to the console management output module; when the second risk analysis result is risky, the PK will be suspended or the PK result will be canceled, and the risky video will be deleted from the video pool and a warning message will be sent to the console management output module.
[0013] Preferably, the console management output module receives the warning information sent by the likes data risk warning module, sends control instructions through the console, monitors the data changes of risky videos in real time, completes the instruction when the console sends an instruction to remove the video, and sends the reason for the removal to the user terminal, thereby completing the management of the children's video likes PK.
[0014] A method for managing likes for children's videos on the Internet, comprising the following steps: Step S01: Evaluate whether the video enters the video pool by analyzing the video data; Step S02: Perform PK object matching on the videos in the video pool and monitor the changes in the likes data of the PK objects in real time; Step S03: performing a first risk analysis and a second risk analysis on the video data; Step S04: sending warning information to a control console based on the first risk analysis result and the second risk analysis result; Step S05: The console sends a control instruction to complete the management of the children's video likes PK.
[0015] Technical effects and advantages of the present invention: The present invention completes the management of children's video likes PK by providing a children's video likes data statistics module, a children's video PK object matching module, a likes data risk analysis module, a likes data risk warning module and a console management output module, so that managers can conveniently monitor and manage the entire process of children's video likes PK; By analyzing the video data, it is evaluated whether the video has entered the video pool, and the videos in the video pool are transformed from the initial video pool sequence to the recombined video pool sequence. PK object matching is performed and the changes in the PK object likes data are monitored in real time. At the same time, risk analysis of the video data is performed. It not only covers the analysis of video data, the construction of the video pool, and the matching of PK objects, but also includes the risk analysis and early warning mechanism of the likes data, forming a closed-loop management process to promptly discover and handle abnormal situations. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] Figure 1 This is a structural diagram of an Internet children's video like PK management system.
[0017] Figure 2 This is a flowchart of a method for managing likes for children's videos on the Internet. DETAILED DESCRIPTION
[0018] The technical solutions of the present invention will be described clearly and completely below in conjunction with the drawings in the present invention. In addition, the forms of the various structures described in the following embodiments are merely examples. The Internet children's video likes PK management system and method involved in the present invention are not limited to the various structures described in the following embodiments. All other implementations obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.
[0019] like Figure 1 As shown, the present invention provides an Internet children's video likes PK management system, including: a children's video likes data statistics module, a children's video PK object matching module, a likes data risk analysis module, a likes data risk warning module and a console management output module; The children's video likes data statistics module includes a video review unit, a video data collection unit and a video quality assessment unit. The module analyzes the video data to evaluate whether the video has entered the video pool and transmits the evaluation result to the children's video PK object matching module; The children's video PK object matching module receives the evaluation results transmitted by the children's video likes data statistics module, performs PK object matching on the videos in the video pool and monitors the changes in the PK object likes data in real time; The likes data risk analysis module includes a first unit and a second unit. The first unit performs a first risk analysis on the video data in the children's video likes data statistics module, and the second unit performs a second risk analysis on the likes data monitored by the children's video PK object matching module, and transmits the analysis results to the likes data risk warning module; The likes data risk warning module sends warning information to the console management output module based on the first risk analysis result and the second risk analysis result of the likes data risk analysis module; The console management output module receives the warning information sent by the likes data risk warning module, and sends control instructions through the console to complete the management of the children's video likes PK.
[0020] In this embodiment, it should be specifically explained that in the children's video likes data statistics module, the video review unit is responsible for reviewing the uploaded children's videos and publishing the videos after passing the review standards. The video data collection unit is responsible for collecting data on the videos and transmitting the collected likes data to the video quality assessment unit to assess the quality of the videos.
[0021] In this embodiment, it should be specifically explained that the video quality evaluation unit evaluates the video quality as follows: Step S1: Set the video data collection deadline. The time period from the video release to the video data collection deadline is the first stage. Divide the first stage of the video to be evaluated into n sub-time periods, where i=1, 2, 3, ..., n, and i represents the number of each sub-video in the first stage; Step S2: Collect the number of likes received in each sub-time period in the first stage of the video to be evaluated, and sum the number of likes received to obtain the total number of likes received in the first stage of the video to be evaluated. The calculation formula is: ,in Indicates the total number of likes received by the video to be evaluated in the first stage. Indicates the number of likes received in each sub-time period in the first stage of the video to be evaluated; Step S3: The total number of likes received in the first phase of the video to be evaluated obtained in step S2 and the preset threshold of likes For comparison, if the total number of likes received in the first stage of the video to be evaluated is Greater than or equal to the preset threshold of likes , then the video quality assessment unit will assess the quality of the video; on the contrary, if the total number of likes received in the first stage of the video to be assessed is Less than the preset threshold of likes , the video to be evaluated does not enter the video quality evaluation unit; Step S4: The video quality assessment unit receives the video to be assessed transmitted in step S3 and performs quality assessment on the video. The calculation formula is: ,in Indicates the quality evaluation value of the video to be evaluated. Indicates the quality impact factor of the video to be evaluated, represents a constant, Indicates the average number of likes received in each sub-time period during the first phase of the video to be evaluated. The quality assessment value of the video to be evaluated is used to determine the degree of deviation of the number of likes received in each sub-time period during the first phase of the video to be evaluated from the average value. A larger quality assessment value of the video to be evaluated indicates a greater degree of deviation from the average level. Step S5: The quality evaluation value of the video to be evaluated The threshold for entering the video pool For comparison, if the quality evaluation value of the video to be evaluated is Less than or equal to the threshold for entering the video pool , then the video to be evaluated will be put into the video pool. On the contrary, if the quality evaluation value of the video to be evaluated is Greater than the threshold for entering the video pool , the video to be evaluated will not be put into the video pool.
[0022] In this embodiment, it should be specifically explained that, in the children's video PK object matching module, the specific contents of performing PK object matching on the videos in the video pool are as follows: Arrange the m videos in the video pool in sequence according to the time when the videos enter the video pool to form an initial video pool sequence, where m≥2. When m<2, no video pool is formed. The second phase of likes statistics is performed on the m videos in the initial video pool. The second phase represents the time period from the video data collection deadline set by the video quality assessment unit to the time when the video enters the video pool to form the initial video pool sequence. The likes distribution coefficient of each video in the initial video pool is calculated using the following formula: ,in Represents the likes distribution coefficient of each video in the initial video pool, represents the impact factor of the number of likes, Indicates the total number of likes received by each video in the initial video pool in the first stage. Indicates the total number of likes received by each video in the initial video pool in the second phase. Indicates the statistical time of the first stage of each video in the initial video pool. Indicates the statistical time of the second stage of each video in the initial video pool. Indicates the playback duration of each video in the initial video pool. Indicates the preset number of likes corresponding to the playback time of each video in the initial video pool; According to the likes distribution coefficient of each video in the initial video pool, each video is arranged in descending order to form a reorganized video pool sequence. Adjacent videos are extracted according to the adjacent video PK principle to generate PK video matching pairs, and the changes in the likes data of the PK objects are monitored in real time.
[0023] In this embodiment, it should be specifically explained that in the likes data risk warning module, the first unit performs a first risk analysis on the video data in the children's video likes data statistics module to calculate a first risk coefficient of the first stage of the video to be evaluated; The second unit performs a second risk analysis on the likes data monitored by the children's video PK object matching module and calculates a second risk coefficient.
[0024] In this embodiment, it should be specifically explained that the calculation formula for the first risk coefficient of the first stage of the video to be evaluated is: ,in represents the first risk coefficient of the first stage of the video to be evaluated, n represents the number of sub-time periods divided into the first stage of the video to be evaluated, Indicates the number of likes received in each sub-time period in the first stage of the video to be evaluated; The first risk factor of the first stage of the video to be evaluated Compared with the preset risk factor threshold range, if the first risk factor of the first stage of the video to be evaluated is If the risk factor is within the preset threshold, the data is judged to be risk-free. Otherwise, if the first risk factor of the first stage of the video to be evaluated is If the data is not within the preset risk factor threshold, it is judged to be risky.
[0025] In this embodiment, it should be specifically explained that the specific content of calculating the second risk coefficient is as follows: Divide the videos in the video pool into n sub-time periods, where i = 1, 2, 3, ..., n, and i represents the number of each sub-video; Analyze the growth rate of likes data for each sub-video, and the calculation formula is: ,in Indicates the growth rate of likes data for each sub-video, Indicates the number of likes for each sub-video; The second risk factor of the videos in the video pool is calculated based on the growth rate of likes data of each sub-video. The calculation formula is: ,in Indicates the second risk factor of the videos in the video pool, Indicates the growth rate of likes data for each sub-video, represents the maximum growth rate of likes data of each sub-video, e represents a constant, Indicates the stability coefficient of the videos in the video pool. The growth rate is calculated by the number of likes in the current time period and the previous time period. Therefore, i≠1, and the value of i starts from 2. The second risk factor of the video in the video pool Compare with the preset risk factor threshold range, if the second risk factor of the video in the video pool is If the risk factor is within the preset threshold, the data is judged to be risk-free. Otherwise, if the second risk factor of the video in the video pool is If the data is not within the preset risk factor threshold, it is judged to be risky.
[0026] In this embodiment, it should be specifically explained that in the likes data risk warning module, based on the first risk analysis result and the second risk analysis result of the likes data risk analysis module, when the first risk analysis result is risky, the video will not enter the video pool, and a warning message will be sent to the console management output module; when the second risk analysis result is risky, the PK will be suspended or the PK result will be canceled, and the risky video will be deleted from the video pool and a warning message will be sent to the console management output module.
[0027] In this embodiment, it should be specifically explained that the console management output module receives the warning information sent by the likes data risk warning module, sends control instructions through the console, monitors the data changes of risky videos in real time, completes the instruction when the console sends an instruction to remove the video, and sends the reason for the removal to the user terminal, thereby completing the management of the children's video likes PK.
[0028] like Figure 2 As shown, in this embodiment, it should be specifically explained that a method for managing likes for children's videos on the Internet includes the following steps: Step S01: Evaluate whether the video enters the video pool by analyzing the video data; Step S02: Perform PK object matching on the videos in the video pool and monitor the changes in the likes data of the PK objects in real time; Step S03: performing a first risk analysis and a second risk analysis on the video data; Step S04: sending warning information to a control console based on the first risk analysis result and the second risk analysis result; Step S05: The console sends a control instruction to complete the management of the children's video likes PK.
[0029] In this embodiment, it should be specifically explained that the difference between this embodiment and the prior art is that this embodiment completes the management of the children's video likes PK by providing a children's video likes data statistics module, a children's video PK object matching module, a likes data risk analysis module, a likes data risk warning module, and a console management output module, so that managers can conveniently monitor and manage the entire process of the children's video likes PK; By analyzing the video data, it is evaluated whether the video has entered the video pool, and the videos in the video pool are transformed from the initial video pool sequence to the recombined video pool sequence. PK object matching is performed and the changes in the PK object likes data are monitored in real time. At the same time, risk analysis of the video data is performed. It not only covers the analysis of video data, the construction of the video pool, and the matching of PK objects, but also includes the risk analysis and early warning mechanism of the likes data, forming a closed-loop management process to promptly discover and handle abnormal situations.
[0030] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.
[0031] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.
Claims
1. An Internet children's video likes PK management system, characterized by: include: Children's video likes data statistics module, children's video PK object matching module, likes data risk analysis module, likes data risk warning module and console management output module; The children's video likes data statistics module includes a video review unit, a video data collection unit and a video quality assessment unit. The module analyzes the video data to evaluate whether the video has entered the video pool and transmits the evaluation result to the children's video PK object matching module; The children's video PK object matching module receives the evaluation results transmitted by the children's video likes data statistics module, performs PK object matching on the videos in the video pool and monitors the changes in the PK object likes data in real time; The likes data risk analysis module includes a first unit and a second unit. The first unit performs a first risk analysis on the video data in the children's video likes data statistics module, and the second unit performs a second risk analysis on the likes data monitored by the children's video PK object matching module, and transmits the analysis results to the likes data risk warning module; The likes data risk warning module sends warning information to the console management output module based on the first risk analysis result and the second risk analysis result of the likes data risk analysis module; The console management output module receives the warning information sent by the likes data risk warning module, and sends control instructions through the console to complete the management of the children's video likes PK.
2. The Internet children's video like PK management system according to claim 1, characterized in that: In the children's video likes data statistics module, the video review unit is responsible for reviewing the uploaded children's videos and publishing the videos after passing the review standards. The video data collection unit is responsible for collecting data on the videos and transmitting the collected likes data to the video quality assessment unit to assess the quality of the videos.
3. The Internet children's video like PK management system according to claim 2, characterized in that: The video quality evaluation unit evaluates the video quality as follows: Step S1: Set the video data collection deadline. The time period from the video release to the video data collection deadline is the first stage. Divide the first stage of the video to be evaluated into n sub-time periods, where i=1, 2, 3, ..., n, and i represents the number of each sub-video in the first stage; Step S2: Collect the number of likes received in each sub-time period in the first stage of the video to be evaluated, and sum the number of likes received to obtain the total number of likes received in the first stage of the video to be evaluated. The calculation formula is: ,in Indicates the total number of likes received by the video to be evaluated in the first stage. Indicates the number of likes received in each sub-time period in the first stage of the video to be evaluated; Step S3: The total number of likes received in the first phase of the video to be evaluated obtained in step S2 and the preset threshold of likes For comparison, if the total number of likes received in the first stage of the video to be evaluated is Greater than or equal to the preset threshold of likes , the video quality is evaluated by the video quality evaluation unit; otherwise, the video to be evaluated does not enter the video quality evaluation unit; Step S4: The video quality assessment unit receives the video to be assessed transmitted in step S3 and performs quality assessment on the video. The calculation formula is: ,in Indicates the quality evaluation value of the video to be evaluated. Indicates the quality impact factor of the video to be evaluated, represents a constant, Indicates the average number of likes received in each sub-time period in the first stage of the video to be evaluated; Step S5: The quality evaluation value of the video to be evaluated The threshold for entering the video pool For comparison, if the quality evaluation value of the video to be evaluated is Less than or equal to the threshold for entering the video pool , the video to be evaluated will be put into the video pool, otherwise, the video to be evaluated will not be put into the video pool.
4. The Internet children's video like PK management system according to claim 1, characterized in that: In the children's video PK object matching module, the specific contents of PK object matching for videos in the video pool are as follows: Arrange the m videos in the video pool in sequence according to the time when the videos enter the video pool to form an initial video pool sequence, where m≥2. When m<2, no video pool is formed. The second phase of likes statistics is performed on the m videos in the initial video pool. The second phase represents the time period from the video data collection deadline set by the video quality assessment unit to the time when the video enters the video pool to form the initial video pool sequence. The likes distribution coefficient of each video in the initial video pool is calculated using the following formula: ,in Represents the likes distribution coefficient of each video in the initial video pool, represents the impact factor of the number of likes, Indicates the total number of likes received by each video in the initial video pool in the first stage. Indicates the total number of likes received by each video in the initial video pool in the second phase. Indicates the statistical time of the first stage of each video in the initial video pool. Indicates the statistical time of the second stage of each video in the initial video pool. Indicates the playback duration of each video in the initial video pool. Indicates the preset number of likes corresponding to the playback time of each video in the initial video pool; According to the likes distribution coefficient of each video in the initial video pool, each video is arranged in descending order to form a reorganized video pool sequence. Adjacent videos are extracted according to the adjacent video PK principle to generate PK video matching pairs, and the changes in the likes data of the PK objects are monitored in real time.
5. The Internet children's video like PK management system according to claim 1, characterized in that: In the likes data risk warning module, the first unit performs a first risk analysis on the video data in the children's video likes data statistics module to calculate a first risk coefficient of the first stage of the video to be evaluated; The second unit performs a second risk analysis on the likes data monitored by the children's video PK object matching module and calculates a second risk coefficient.
6. The Internet children's video like PK management system according to claim 5, characterized in that: The first risk coefficient of the first stage of the video to be evaluated is calculated using the following formula: ,in represents the first risk coefficient of the first stage of the video to be evaluated, n represents the number of sub-time periods divided into the first stage of the video to be evaluated, Indicates the number of likes received in each sub-time period in the first stage of the video to be evaluated; The first risk factor of the first stage of the video to be evaluated Compared with the preset risk factor threshold range, if the first risk factor of the first stage of the video to be evaluated is If the data is within the preset risk factor threshold, it is judged to be risk-free; otherwise, it is judged to be risky.
7. The Internet children's video like PK management system according to claim 5, characterized in that: The specific content of calculating the second risk coefficient is as follows: Divide the videos in the video pool into n sub-time periods, where i = 1, 2, 3, ..., n, and i represents the number of each sub-video; Analyze the growth rate of likes data for each sub-video, and calculate the second risk coefficient of the videos in the video pool based on the growth rate of likes data for each sub-video. The calculation formula is: ,in Indicates the second risk factor of the videos in the video pool, Indicates the growth rate of likes data for each sub-video, represents the maximum growth rate of likes data of each sub-video, e represents a constant, Indicates the stability coefficient of the video in the video pool; The second risk factor of the video in the video pool Compare with the preset risk factor threshold range, if the second risk factor of the video in the video pool is If the data is within the preset risk factor threshold, it is judged to be risk-free; otherwise, it is judged to be risky.
8. The Internet children's video like PK management system according to claim 1, characterized in that: In the likes data risk warning module, based on the first risk analysis result and the second risk analysis result of the likes data risk analysis module, if the first risk analysis result indicates that there is a risk, the video will not be included in the video pool, and a warning message will be sent to the console management output module; When the second risk analysis result is risky, PK is suspended or the PK result is canceled, and the risk video is deleted from the video pool and an early warning message is sent to the console management output module.
9. The Internet children's video like PK management system according to claim 1, characterized in that: The console management output module receives the warning information sent by the likes data risk warning module, sends control instructions through the console, monitors the data changes of risky videos in real time, completes the instruction when the console sends an instruction to remove the video, and sends the reason for the removal to the user terminal, thereby completing the management of the children's video likes PK.
10. A method for managing the likes of children's videos on the Internet, using the method according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step S01: Evaluate whether the video enters the video pool by analyzing the video data; Step S02: Perform PK object matching on the videos in the video pool and monitor the changes in the likes data of the PK objects in real time; Step S03: performing a first risk analysis and a second risk analysis on the video data; Step S04: sending warning information to a control console based on the first risk analysis result and the second risk analysis result; Step S05: The console sends a control instruction to complete the management of the children's video likes PK.