A Visual Recognition Method and System for Grey-Industry Game Accounts

Abstract

The present invention provides a method and system for visual identification of game grey-production accounts. The first standard deviation of each login timestamp array of each user is calculated through the standardized login timestamp arrays of each user. At the same time, a login time interval array is constructed based on the login time intervals of each user to calculate the second standard deviation. Then, a visual scatter plot is constructed with each first standard deviation as the row coordinate and each second standard deviation as the column coordinate. Finally, according to the user's box selection operation, it is analyzed whether the density of the box-selected area on the scatter plot is greater than the density of the surrounding area. If the density of the box-selected area is greater than the density of the surrounding area, the accounts corresponding to the points within the box-selected area are blocked and the scatter plot is updated. It fully considers the user's login preferences on the time axis and the user's preferences for login time intervals, can better identify and visually display game grey-production accounts, and improves the accuracy and efficiency of blocking grey-production accounts.

Description

Technical Field

[0001] The present invention relates to the field of Internet technologies, and more particularly, to a method and system for visually identifying game gray production accounts. Background Art

[0002] Currently, almost all operations of cultivation games are extremely troubled by gray production. Gray production teams "brush numbers" in batches through scripts and programs. This not only causes economic losses to the games, but also greatly interferes with operation data, leading to incorrect decisions by operations. Currently, for gray production users, most are found through outlier data, multiple accounts corresponding to the same IP address, multiple accounts corresponding to the same device, etc. Or corresponding account suspension rules are formulated through the buried point data of the games. However, with the update of technologies, many teams conduct countermeasures by modifying device numbers and dynamically dialing to change addresses. Therefore, a solution is needed to improve the accuracy and efficiency of gray production account suspension, so as to better purify the game environment. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for visually identifying game gray production accounts, so as to achieve the technical effect of improving the accuracy and efficiency of gray production account suspension.

[0004] In a first aspect, the present invention provides a method for visually identifying game gray production accounts, including: S1. Obtain the login times in all user login information tables of a target game during a to-be-searched time period;

[0005] S2. Standardize the login times of each user in the form of timestamps to obtain a login timestamp array corresponding to each user; at the same time, construct a login time interval array corresponding to each user according to the login time intervals of each user;

[0006] S3. Calculate the first standard deviation of each of the login timestamp arrays; at the same time, calculate the second standard deviation of each of the login time interval arrays;

[0007] S4. Use each of the first standard deviations as the row coordinates and each of the second standard deviations as the column coordinates to construct a visual scatter plot;

[0008] S5. Receive a box selection operation of a user in the scatter plot and analyze whether the density of the box selected area is greater than the density of the surrounding areas; if the density of the box selected area is greater than the density of the surrounding areas, suspend the accounts corresponding to the points in the box selected area and update the scatter plot.

[0009] Optionally, the method further includes: S6. Process all user login information tables of subsequent multiple time periods according to the steps of S1-S5 and update the visual scatter plot.

[0010] Optionally, the execution process of S6 processes all user login information tables for the subsequent two time periods at least according to the time length of the to-be-searched time period.

[0011] Optionally, the execution steps of S4 include: First, import each of the first standard deviations and each of the second standard deviations into the Tableau visualization processing platform; Second, set each of the first standard deviations as rows and each of the second standard deviations as columns, and change the corresponding attributes to "dimensions"; Then, set the display shape and size of each point in the scatter plot and set the corresponding opacity; Finally, filter users with the number of logins less than a preset value and adjust the boundaries of the horizontal and vertical axes of the chart to obtain a complete scatter plot.

[0012] Optionally, the preset value is not less than 3.

[0013] In a second aspect, the present invention provides a visualization recognition system for game gray production accounts, including:

[0014] An acquisition module, configured to acquire the login time in all user login information tables of a target game during a to-be-searched time period;

[0015] A processing module, configured to standardize the login time of each user in the form of a time stamp to obtain a login time stamp array corresponding to each user; at the same time, construct a login time interval array corresponding to each user according to the login time interval of each user;

[0016] A calculation module, configured to calculate the first standard deviation of each of the login time stamp arrays; at the same time, calculate the second standard deviation of each of the login time interval arrays;

[0017] A visualization display module, configured to construct a visual scatter plot with each of the first standard deviations as the row coordinates and each of the second standard deviations as the column coordinates;

[0018] An analysis module, configured to receive a box selection operation of a user in the scatter plot and analyze whether the density of the box selection area is greater than the density of the surrounding area; if the density of the box selection area is greater than the density of the surrounding area, block the accounts corresponding to the points in the box selection area and update the scatter plot.

[0019] In a third aspect, the present invention provides a computer-readable storage medium, on which instructions are stored, and when the instructions are executed by a processor, the above-mentioned method is implemented.

[0020] In a fourth aspect, the present invention provides an electronic device, including a processor and a memory connected to the processor; a computer program is stored on the memory; the processor is configured to execute the computer program in the memory to implement the above-mentioned method steps.

[0021] The beneficial effects that the present invention can achieve are as follows: The method for visual recognition of game gray production accounts provided by the present invention calculates the first standard deviation of each login timestamp array through the standardized login timestamp arrays of each user; at the same time, a login time interval array is constructed based on the login time intervals of each user to calculate the second standard deviation; then, a visual scatter plot is constructed with each first standard deviation as the row coordinate and each second standard deviation as the column coordinate; finally, according to the user's box selection operation, it is analyzed whether the density of the boxed area on the scatter plot is greater than the density of the surrounding area. If the density of the boxed area is greater than the density of the surrounding area, the accounts corresponding to the points within the boxed area are blocked and the scatter plot is updated; in this way, the preferences of users for logging in on the time axis and the preferences of users for login time intervals are fully considered, which can better identify and visually display game gray production accounts, and improve the accuracy and efficiency of blocking gray production accounts. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required to be used in the embodiments of the present invention. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0023] Figure 1 It is a schematic flowchart of a method for visual recognition of game gray production accounts provided by an embodiment of the present invention;

[0024] Figure 2 It is a schematic topological structure diagram of a system for visual recognition of game gray production accounts provided by an embodiment of the present invention.

[0025] Icons: 10 - Visual recognition system; 100 - Acquisition module; 200 - Processing module; 300 - Calculation module; 400 - Visual display module; 500 - Analysis module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] The following will describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention.

[0027] It should be noted that: Similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0028] Please refer to Figure 1, Figure 1 It is a schematic flowchart of a method for visual identification of game grey production accounts provided by an embodiment of the present invention.

[0029] In one implementation manner, an embodiment of the present invention provides a method for visual identification of game grey production accounts, and the specific content is as follows.

[0030] S1. Obtain the login times in the login information tables of all users of the target game during the period to be searched.

[0031] Exemplarily, all user login information tables during the period to be searched can be directly obtained from the background operation data of the target game, or can be copied from the server of the target game through a USB flash drive or a mobile hard disk, etc. After obtaining all user login information tables of the target game, the login times of each user can be read from the user login information table and then stored in the form of an Excel table.

[0032] S2. Standardize the login times of each user in the form of time stamps to obtain an array of login time stamps corresponding to each user; at the same time, construct an array of login time intervals corresponding to each user according to the intervals of the login times of each user.

[0033] In one implementation manner, when standardizing the login times of each user in the form of time stamps, it can be calculated in the following way:

[0034]

[0035] In the formula, standard_ts represents the standardized time stamp; standard_time represents the time stamp corresponding to the start time of the period to be searched; end_time represents the time stamp corresponding to the end time of the period to be searched; ts represents the time stamps corresponding to the login times of each user. Example: In the login table of a certain game in April, the time stamp of April 1 is used as standard_time, and the time stamp of April 30 is used as end_time. User A logged in on April 6, April 15, April 21, April 24, and April 27 (the time stamps are used in actual calculation). The result of the standardized login time stamp array obtained by the above processing method is standardtimelist = [0.2, 0.5, 0.7, 0.8, 0.9]. The result of the login time interval array after the above processing method is intervaltimelist = [9, 6, 3, 3] (in actual calculation, the result of subtracting time stamps is in seconds).

[0036] S3. Calculate the first standard deviation of each of the arrays of login time stamps; at the same time, calculate the second standard deviation of each of the arrays of login time intervals.

[0037] Specifically, after obtaining each standardized login timestamp array, the average value of each login timestamp array can be further calculated, and then the corresponding first standard deviation can be calculated based on this average value. After obtaining the login interval array, the average value of each login interval array can be further calculated, and then the corresponding first standard deviation can be calculated based on this average value.

[0038] S4. Use each of the first standard deviations as the row coordinates and each of the second standard deviations as the column coordinates to construct a visual scatter plot.

[0039] In one implementation, the above scatter plot can be obtained through processing on the Tableau visualization processing platform. The specific operations are as follows: First, import each of the first standard deviations and each of the second standard deviations into the Tableau visualization processing platform; second, set each of the first standard deviations as the row and each of the second standard deviations as the column, and change the corresponding attributes to "dimensions"; then, set the display shape and size of each point in the scatter plot, and set the corresponding opacity; finally, filter users with a login count less than a preset value and adjust the boundaries of the horizontal and vertical axes of the chart to obtain a complete scatter plot.

[0040] Exemplarily, the opacity can be adjusted within the range of 1% to 10%, and the preset value of the login count is set to a value not less than 3. By setting the preset value, users with relatively low login frequencies can be filtered out. In this way, both the data processing volume can be reduced and the result can be made more accurate.

[0041] S5. Receive the user's box selection operation in the scatter plot and analyze whether the density of the box selected area is greater than the density of the surrounding area; if the density of the box selected area is greater than the density of the surrounding area, then block the accounts corresponding to the points in the box selected area and update the scatter plot.

[0042] Exemplarily, the user can box select each area in the scatter plot on the Tableau visualization processing platform, and then obtain the density within the box selected area through analysis. If the density of the box selected area is greater than the density of the surrounding area, then block the accounts corresponding to the points in the box selected area and update the scatter plot.

[0043] In one implementation, to more comprehensively block gray production accounts, the above method further includes:

[0044] S6. Process all user login information tables for subsequent multiple time periods according to the steps of S1 - S5 and update the visual scatter plot.

[0045] Specifically, the above execution process can process all user login information tables of the subsequent two time periods at least according to the time length of the time period to be searched.

[0046] Please refer to Figure 2 , Figure 2 which is a schematic topological structure diagram of a visual recognition system for game gray production accounts provided by an embodiment of the present invention.

[0047] In one implementation, an embodiment of the present invention further provides a visual recognition system 10 for game gray production accounts. The visual recognition system 10 includes:

[0048] An acquisition module 100, configured to acquire the login time in all user login information tables of the target game during the time period to be searched;

[0049] A processing module 200, configured to standardize the login time of each user in the form of a time stamp to obtain a login time stamp array corresponding to each user; and simultaneously construct a login time interval array corresponding to each user according to the interval of the login time of each user;

[0050] A calculation module 300, configured to calculate the first standard deviation of each login time stamp array; and simultaneously calculate the second standard deviation of each login time interval array;

[0051] A visual display module 400, configured to construct a visual scatter plot with each first standard deviation as the row coordinate and each second standard deviation as the column coordinate;

[0052] An analysis module 500, configured to receive a box selection operation of a user in the scatter plot and analyze whether the density of the box selection area is greater than the density of the surrounding area; if the density of the box selection area is greater than the density of the surrounding area, then block the accounts corresponding to the points in the box selection area and update the scatter plot.

[0053] Furthermore, an embodiment of the present invention further provides a computer-readable storage medium, on which instructions are stored. The instructions are characterized in that when the instructions are executed by a processor, the above method is implemented.

[0054] Furthermore, an embodiment of the present invention further provides an electronic device, which includes a processor and a memory connected to the processor; a computer program is stored on the memory; the processor is configured to execute the computer program in the memory to implement the above method steps.

[0055] In summary, the embodiments of the present invention provide a method and system for visual recognition of game gray production accounts. The first standard deviation of each login timestamp array is calculated through the login timestamp arrays of each user after standardization processing. At the same time, a login time interval array is constructed based on the login time intervals of each user, and the second standard deviation is calculated. Then, a visual scatter plot is constructed with each first standard deviation as the row coordinate and each second standard deviation as the column coordinate. Finally, according to the user's box selection operation, it is analyzed whether the density of the boxed area on the scatter plot is greater than the density of the surrounding area. If the density of the boxed area is greater than the density of the surrounding area, the accounts corresponding to the points within the boxed area are blocked and the scatter plot is updated. In this way, the preferences of users for logging in on the time axis and the preferences of users for login time intervals are fully considered, which can better identify and visually display game gray production accounts, and improve the accuracy and efficiency of blocking gray production accounts.

[0056] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A visual recognition method for game gray production accounts, characterized in that Including: S1. Obtain the login times in the login information tables of all users of the target game during the period to be searched; S2. Standardize the login times of each user in the way of time stamps to obtain the login time stamp arrays corresponding to each user; at the same time, construct the login time interval arrays corresponding to each user according to the login time intervals of each user; S3. Calculate the first standard deviation of each of the login time stamp arrays; at the same time, calculate the second standard deviation of each of the login time interval arrays; S4. Use each of the first standard deviations as the row coordinates and each of the second standard deviations as the column coordinates to construct a visualized scatter plot; S5. Receive the user's box selection operation in the scatter plot and analyze whether the density of the box selection area is greater than the density of the surrounding area; if the density of the box selection area is greater than the density of the surrounding area, block the accounts corresponding to the points in the box selection area and update the scatter plot.

2. The method according to claim 1, characterized in that The method further includes: S6. Process the login information tables of all users in multiple subsequent periods according to the steps of S1-S5 and update the visualized scatter plot.

3. The method according to claim 2, wherein The execution process of S6 processes the login information tables of all users in at least two subsequent periods according to the time length of the period to be searched.

4. The method according to claim 1, wherein The execution steps of S4 include: First, import each of the first standard deviations and each of the second standard deviations into the Tableau visualization processing platform; secondly, set each of the first standard deviations as the row and each of the second standard deviations as the column, and change the corresponding attributes to "dimension"; then, set the display shapes and sizes of the points in the scatter plot, and set the corresponding opacity; finally, filter the users with the login times less than the preset value and adjust the boundaries of the horizontal and vertical axes of the chart to obtain a complete scatter plot.

5. The method according to claim 4, characterized in that The preset value is not less than 3.

6. A visual recognition system for game gray production accounts, characterized in that, Including: An acquisition module, configured to obtain the login times in the login information tables of all users of the target game during the period to be searched; A processing module, configured to standardize the login times of each user in the way of time stamps to obtain the login time stamp arrays corresponding to each user; at the same time, construct the login time interval arrays corresponding to each user according to the login time intervals of each user; A calculation module, configured to calculate the first standard deviation of each of the login time stamp arrays; at the same time, calculate the second standard deviation of each of the login time interval arrays; A visualization display module, configured to use each of the first standard deviations as the row coordinates and each of the second standard deviations as the column coordinates to construct a visualized scatter plot; An analysis module, configured to receive the user's box selection operation in the scatter plot and analyze whether the density of the box selection area is greater than the density of the surrounding area; if the density of the box selection area is greater than the density of the surrounding area, block the accounts corresponding to the points in the box selection area and update the scatter plot.

7. A computer-readable storage medium having instructions stored thereon, characterized in that, When the instruction is executed by the processor, the method according to any one of claims 1-5 is implemented.

8. An electronic device, characterized in that, Including a processor and a memory connected to the processor; a computer program is stored on the memory; the processor is configured to execute the computer program in the memory to implement the method steps according to any one of claims 1-5.

Images