Method for reducing error rate of popup operation, electronic equipment and computer storage medium

Abstract

The invention discloses a method for reducing the error rate of pop-up operation, electronic equipment and a computer storage medium, and the method comprises the steps: learning an operation case of a target application, an association relationship between an application function and a pop-up function based on a preset artificial intelligence algorithm, so as to construct pop-up operation features of the target application; based on the historical popup operation data of the sample users, a classification rule of user operation groups is constructed, and the classification rule is used for dividing the sample users into multiple user operation groups; determining a target user operation group corresponding to the terminal equipment user based on the classification rule and historical popup operation data of the terminal equipment user; receiving a pop-up window operation which is sent by the terminal device and acts on a first pop-up window of the target application, performing operation prediction on the first pop-up window based on the target user operation group and the pop-up window operation characteristics of the target application, and determining a prediction operation; and if the predicted operation is inconsistent with the popup operation, sending prompt information to the terminal equipment, so that the error probability of the user in the popup operation can be reduced.

Description

Technical Field

[0001] This application relates to the field of terminal technology, and in particular to a method for reducing the error rate of pop-up window operations, an electronic device, and a computer storage medium. Background Technology

[0002] Currently, when users click on pop-ups within applications, they often make mistakes because they don't carefully read the pop-up content or are in a hurry to close it. For example, after confirming an upgrade, a pop-up window asks whether to allow the application to install the program; users often mistakenly click the "Deny Installation" button on the right. Because of the high rate of accidental clicks on pop-ups, it affects users' subsequent actions. Similarly, in privacy policy pop-ups, users often mistakenly click the "Allow Push Notifications" button and then search for the option to disable push notifications, which also negatively impacts the user experience. Summary of the Invention

[0003] In view of this, embodiments of this application provide a method, electronic device, and computer storage medium for reducing the error rate of pop-up window operations, in order to solve the problem of high error probability of users clicking on pop-ups.

[0004] To address the aforementioned technical problems, the first aspect of this application provides the following technical solution: a method for reducing the error rate of pop-up window operations, applied to a server, comprising: The operation use cases, application functions and pop-up functions of the target application are learned based on a preset artificial intelligence algorithm to construct the pop-up operation features of the target application. Based on the historical pop-up operation data of multiple sample users, a classification rule for user operation groups is constructed. The classification rule is used to divide the multiple sample users into multiple user operation groups. Based on the classification rules and the historical pop-up operation data of terminal device users, the target user operation group corresponding to the terminal device user is determined from the multiple user operation groups. Receive a pop-up operation sent by the terminal device that acts on the first pop-up window of the target application, predict the operation of the first pop-up window based on the target user operation group and the pop-up operation characteristics of the target application, and determine the predicted operation; If the prediction operation is inconsistent with the pop-up operation, a prompt message is sent to the terminal device.

[0005] In one possible design, the classification rules for user action groups, based on historical pop-up operation data from multiple sample users, specifically include: The KMeans clustering algorithm was used to identify features in the historical pop-up operation data of the multiple sample users, resulting in feature identification data. The feature identification data is clustered to construct classification rules for user operation groups, where the mapping relationship between a sample user and a user operation group is one-to-one.

[0006] In one possible design, the user operation groups include positive operation groups, negative operation groups, hesitant operation groups, and erroneous operation groups. The step of determining the target user operation group corresponding to the terminal device user from these multiple user operation groups, based on the classification rules and the historical pop-up operation data of the terminal device user, specifically includes: Obtain historical pop-up operation data of terminal device users; Based on the classification rules and the historical pop-up operation data, the target user operation group corresponding to the terminal device user is determined from the positive operation group, the negative operation group, the hesitant operation group, and the erroneous operation group.

[0007] In one possible design, after receiving the pop-up operation of the first pop-up window acting on the target application sent by the terminal device, the method further includes: Predict the probability of erroneous operation of the pop-up operation based on the pop-up operation characteristics of the target user operation group and the target application; If the probability of the erroneous operation is greater than the preset probability, the prompt message is sent to the terminal device.

[0008] In one possible design, the prompt information includes a predicted operation determined by the operation prediction of the first pop-up window.

[0009] In one possible design, the step of sending a prompt message to the terminal device if the prediction operation is inconsistent with the pop-up operation specifically includes: Compare the pop-up operation with the prediction operation; If the prediction operation is inconsistent with the pop-up operation, a prompt message indicating that the pop-up operation may be incorrect is sent to the terminal device to trigger the terminal device to display a prompt window. The prompt window includes the prompt message indicating that the pop-up operation may be incorrect and the prediction operation, and the prompt window is displayed on top of the first pop-up.

[0010] In one possible design, after sending a message indicating a possible error in the pop-up operation to the terminal device, the method further includes: Receive information sent by the terminal device that is used to confirm the execution of the pop-up operation in the prompt window; Send a solution to the erroneous operation to the terminal device to trigger the terminal device to display the solution in a floating window.

[0011] In one possible design, sending the notification message to the terminal device further includes: Send a solution to the erroneous operation to the terminal device to trigger the terminal device to display the solution in a floating window.

[0012] Accordingly, this application also provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the computer program is executed by the processor, it implements the steps of a method for reducing the error rate of pop-up window operations as described in any of the preceding claims.

[0013] Accordingly, this application also provides a computer storage medium storing a program for a method of reducing the error rate of pop-up window operations. When the program for reducing the error rate of pop-up window operations is executed by a processor, it implements the steps of the method for reducing the error rate of pop-up window operations as described in any of the preceding claims.

[0014] Compared with related technologies, the method, electronic device, and computer storage medium for reducing pop-up operation error rate proposed in this application embodiment learns the relationship between the operation use cases, application functions, and pop-up functions of the target application based on a preset artificial intelligence algorithm. Based on historical pop-up operation data of multiple sample users, it constructs classification rules for user operation groups. Then, based on the classification rules and the historical pop-up operation data of terminal device users, it determines the target user operation group corresponding to the terminal device user. Based on the target user operation group and the pop-up operation characteristics of the target application, it predicts the operation of the first pop-up acting on the target application. If the predicted operation is inconsistent with the pop-up operation, it sends a prompt message to the terminal device to trigger the display of a prompt window, thereby reducing the pop-up operation error rate. Simultaneously, by responding to the information sent by the terminal device confirming the execution of the pop-up operation in the prompt window, it sends a solution to the error to the terminal device, triggering the terminal device to display the solution as a floating window, thereby improving the user experience. Attached Figure Description

[0015] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0016] Figure 1 This is a flowchart illustrating the first embodiment of a method for reducing the error rate of pop-up window operations according to this application; Figure 2 This is a flowchart illustrating a second embodiment of a method for reducing the error rate of pop-up window operations according to this application; Figure 3 This is a flowchart illustrating a third embodiment of a method for reducing the error rate of pop-up window operations according to this application; Figure 4 This is a flowchart illustrating the fourth embodiment of a method for reducing the error rate of pop-up window operations according to this application; Figure 5 This is a flowchart illustrating the fifth embodiment of a method for reducing the error rate of pop-up window operations according to this application; Figure 6 This is a flowchart illustrating the sixth embodiment of a method for reducing the error rate of pop-up window operations according to this application; Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0017] To make the technical problems, technical solutions, and beneficial effects to be solved by this application clearer and more understandable, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of this application.

[0018] In the following description, the use of suffixes such as "module," "part," or "unit" to denote elements is solely for the purpose of illustration and has no specific meaning in itself. Therefore, "module," "part," or "unit" may be used interchangeably.

[0019] It should be noted that the terms "first," "second," etc., in the specification, claims, and drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0020] Example 1 Figure 1 This is a flowchart of the first embodiment of the method for reducing the error rate of pop-up window operations according to the present invention. A method for reducing the error rate of pop-up window operations, the method being applied to a server, the method may include: S1. Based on a preset artificial intelligence algorithm, learn the relationship between the operation use cases, application functions and pop-up functions of the target application to construct the pop-up operation features of the target application; S2. Based on the historical pop-up operation data of multiple sample users, construct a classification rule for user operation groups. The classification rule is used to divide the multiple sample users into multiple user operation groups. S3. Based on the classification rules and the historical pop-up operation data of the terminal device user, determine the target user operation group corresponding to the terminal device user from the multiple user operation groups; S4. Receive the pop-up operation sent by the terminal device that acts on the first pop-up window of the target application, and predict the operation of the first pop-up window based on the target user operation group and the pop-up operation characteristics of the target application to determine the predicted operation. S5. If the prediction operation is inconsistent with the pop-up operation, send a prompt message to the terminal device.

[0021] In this embodiment, the server can be an independent server or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms. For example, the server can be the server of the target application. The terminal device can have a large number of applications (APPs) installed. These applications can include those pre-installed on the terminal device and those downloaded by the user. During execution, the applications on the terminal device typically push information to the user via pop-ups. This information can include text information and other information related to the window displaying this text information, such as window type, application ID, and package name. The applications can include game applications, live streaming applications, shopping applications, etc., and are not limited thereto.

[0022] In this embodiment, the target application can be at least one of the applications. The operation use case of the target application can be an example of a user interacting with the target application to complete a specific goal / function. The application function is a function possessed by the target application, for example, it may include version upgrade function, privacy permission setting function, etc., and is not limited here. The pop-up function can be a pop-up window function, such as a pop-up prompting whether to update to a new version, whether to allow push notifications, etc., and is not limited here.

[0023] In this embodiment, the relationship between the operation use cases, application functions, and pop-up window functions of the target application can be learned based on a preset artificial intelligence algorithm to construct the pop-up window operation features of the target application. These pop-up window operation features can reflect the pop-up options and their functions contained in each pop-up window within the target application.

[0024] In this embodiment of the application, taking a game application as the target application and a version upgrade as the application function as the application function, the relationship between the version upgrade function of the game application, the pop-up function display of whether the version is updated and the operation can be learned based on a preset artificial intelligence algorithm, so as to construct the pop-up operation features of the game application.

[0025] The beneficial effect of this embodiment is that by receiving the pop-up operation sent by the terminal device to the first pop-up window of the target application, the operation prediction of the first pop-up window is performed based on the operation group of the target user and the pop-up operation characteristics of the target application, the predicted operation is determined, and if the predicted operation is inconsistent with the pop-up operation, a prompt message is sent to the terminal device to trigger the terminal device to display a prompt window, thereby reducing the error rate of pop-up operation.

[0026] Example 2 Figure 2 This is a flowchart of the second embodiment of the method for reducing the error rate of pop-up window operations according to the present invention. Based on the above embodiment, the step of constructing a classification rule for user operation groups based on historical pop-up window operation data of multiple sample users includes: S21. Use the KMeans clustering algorithm to perform feature identification on the historical pop-up operation data of the multiple sample users to obtain feature identification data; S22. Cluster the feature identification data to construct classification rules for user operation groups, wherein the mapping relationship between a sample user and a user operation group is one-to-one.

[0027] In this embodiment, the historical pop-up operation data can be pop-up operation data applied to the target application within a preset time period. The preset time period can be the previous week, the previous month, the previous two months, etc., and is not limited thereto.

[0028] In this embodiment, the user operation group may include a positive operation group, a negative operation group, a hesitant operation group, and an error operation group. The sample user can be a positive operation user, a negative operation user, a hesitant operation user, or an error operation user. The positive operation user can correspond to the positive operation group; the negative operation user can correspond to the negative operation group; the hesitant operation user can correspond to the hesitant operation group; and the error operation user can correspond to the error operation group. It is understood that the user operation group may also include other operation groups, which are not limited here. The sample user may also include other operation users, which are not limited here.

[0029] In the embodiments of this application, the pop-up operation may include positive operation, negative operation, hesitant operation, and error operation.

[0030] In this embodiment, the positive operation group can be the positive operation performed by the user on the pop-up window, such as upgrading the application and / or receiving push notifications from the application; the negative operation group can be the negative operation performed by the user on the pop-up window, such as blocking application upgrades or any advertisements from the application; the hesitant operation group can be the hesitant operation performed by the user on the pop-up window, such as the operation time on the pop-up window exceeding a preset operation time; the error operation group can be the error operation performed by the user on the pop-up window, such as the number of incorrect operations on the pop-up window exceeding a preset number. The error operation can refer to the user mistakenly clicking on a selection in the pop-up window and then searching for a solution to the incorrect selection.

[0031] In this embodiment, the preset operation time can be 10s, 30s, 1 minute, etc., and is not limited thereto. The preset number of times can be preset, such as 2 times, 3 times, 5 times, etc., and is not limited thereto.

[0032] The beneficial effect of this embodiment is that the historical pop-up operation data of the multiple sample users can be obtained through the terminal device, the KMeans clustering algorithm is used to identify the features of the historical pop-up operation data of the multiple sample users to obtain feature identification data, and the feature identification data is clustered to construct the classification rules of user operation groups, so as to divide the multiple sample users into positive operation groups, negative operation groups, hesitant operation groups or error operation groups.

[0033] Example 3 Figure 3 This is a flowchart of the third embodiment of the method for reducing the error rate of pop-up operations according to the present invention. Based on the above embodiment, the user operation group includes a positive operation group, a negative operation group, a hesitant operation group, and an erroneous operation group. The step of determining the target user operation group corresponding to the terminal device user from the multiple user operation groups based on the classification rules and the historical pop-up operation data of the terminal device user specifically includes: S31. Obtain historical pop-up operation data of terminal device users; S32. Based on the classification rules and the historical pop-up operation data, determine the target user operation group corresponding to the terminal device user from the positive operation group, the negative operation group, the hesitant operation group, and the erroneous operation group.

[0034] In the application embodiment, the historical pop-up operation data of the terminal device user can be obtained through the terminal device. Based on the classification rules of the constructed user operation group and the historical pop-up operation data of the terminal device user, the target user operation group corresponding to the terminal device user can be determined from the positive operation group, the negative operation group, the hesitant operation group and the erroneous operation group.

[0035] In one embodiment of the application, for example, if the historical pop-up operation data of the terminal device user is that the historical pop-up operation is to allow application upgrade, i.e., the positive operation, then based on the classification rules and the positive operation data, the target user operation group corresponding to the terminal device user is determined as the positive operation group from the multiple user operation groups.

[0036] In one embodiment of the application, for example, if the historical pop-up operation data of the terminal device user is that the historical pop-up operation is to prohibit application upgrades, i.e., the negative operation, then based on the classification rules and the negative operation data, the target user operation group corresponding to the terminal device user is determined as the negative operation group from the multiple user operation groups.

[0037] In one embodiment of the application, for example, if the historical pop-up operation data of the terminal device user shows that the historical pop-up operation is an operation that takes longer than a preset time, i.e., a hesitation operation, then based on the classification rules and the hesitation operation data, the target user operation group corresponding to the terminal device user is determined as the hesitation operation group from the multiple user operation groups.

[0038] In one embodiment of the application, for example, if the historical pop-up operation data of the terminal device user is such that the number of erroneous operations performed on the pop-up is greater than the preset number, i.e., the erroneous operation, then based on the classification rules and the erroneous operation data, the target user operation group corresponding to the terminal device user is determined as the erroneous operation group from the multiple user operation groups.

[0039] The beneficial effect of this embodiment is that, by determining the target user operation group corresponding to the terminal device user based on the classification rules and the historical pop-up operation data, the error probability of pop-up operation can be predicted and prompt information can be sent in subsequent steps based on the determined target user operation group, so as to reduce the error rate of pop-up operation.

[0040] Example 4 Figure 4 This is a flowchart of the fourth embodiment of the method for reducing the error rate of pop-up window operations according to the present invention. Based on the above embodiment, the step of sending a prompt message to the terminal device if the predicted operation is inconsistent with the pop-up window operation specifically includes: S51. Compare the pop-up operation with the prediction operation; S52. If the prediction operation is inconsistent with the pop-up operation, a prompt message indicating that the pop-up operation may be incorrect is sent to the terminal device to trigger the terminal device to display a prompt window, wherein the prompt window includes the prompt message indicating that the pop-up operation may be incorrect and the prediction operation, and the prompt window is displayed on top of the first pop-up.

[0041] In some embodiments, the prompt window may also include other information. The prompt window is displayed above the first pop-up window for the user to view.

[0042] In this embodiment, the prediction operation can be either the positive operation or the negative operation. The pop-up operation is compared with the prediction operation. If the comparison result is inconsistent, indicating a possible error in the pop-up operation, a warning message indicating a possible error is sent to the terminal device. This triggers the terminal device to display a prompt window including the warning message and the prediction operation, thus alerting the user and reducing the error rate of the pop-up operation.

[0043] In this embodiment of the application, if the prediction operation is consistent with the pop-up operation, no new prompt will be generated, that is, the step of sending prompt information to the terminal device will not be executed.

[0044] In this embodiment of the application, taking the target user operation group corresponding to the determined terminal device user as the negative operation group as an example, the operation prediction of the first pop-up is performed based on the negative operation group and the pop-up operation characteristics of the target application. If the determined predicted operation is the negative operation, the pop-up operation is compared with the negative operation of the predicted operation. If the comparison result is that the pop-up operation is not the negative operation, that is, the predicted operation is inconsistent with the pop-up operation, a prompt message is sent to the terminal device.

[0045] In this embodiment of the application, taking the target user operation group corresponding to the determined terminal device user as the hesitant operation group as an example, the operation prediction of the first pop-up is performed based on the hesitant operation group and the pop-up operation characteristics of the target application. If the determined predicted operation is the negative operation, the pop-up operation is compared with the negative operation of the predicted operation. If the comparison result is that the pop-up operation is not the negative operation, that is, the predicted operation is inconsistent with the pop-up operation, a prompt message is sent to the terminal device.

[0046] In this embodiment of the application, taking the target user operation group corresponding to the determined terminal device user as the hesitant operation group as an example, the operation prediction of the first pop-up is performed based on the hesitant operation group and the pop-up operation characteristics of the target application. If the determined predicted operation is the positive operation, the pop-up operation is compared with the positive operation of the predicted operation. If the comparison result is that the pop-up operation is not the positive operation, that is, the predicted operation is inconsistent with the pop-up operation, a prompt message is sent to the terminal device.

[0047] In this embodiment of the application, taking the target user operation group corresponding to the determined terminal device user as the erroneous operation group as an example, the operation prediction of the first pop-up is performed based on the erroneous operation group and the pop-up operation characteristics of the target application. If the determined predicted operation is the positive operation, the pop-up operation is compared with the positive operation of the predicted operation. If the comparison result is that the pop-up operation is not the positive operation, that is, the predicted operation is inconsistent with the pop-up operation, a prompt message is sent to the terminal device.

[0048] In this embodiment of the application, taking the target user operation group corresponding to the determined terminal device user as the erroneous operation group as an example, the operation prediction of the first pop-up is performed based on the erroneous operation group and the pop-up operation characteristics of the target application. If the determined predicted operation is the negative operation, the pop-up operation is compared with the negative operation of the predicted operation. If the comparison result is that the pop-up operation is not the negative operation, that is, the predicted operation is inconsistent with the pop-up operation, a prompt message is sent to the terminal device.

[0049] The beneficial effect of this embodiment is that, when the predicted operation and the pop-up operation are inconsistent, a prompt message indicating that the pop-up operation may be incorrect is sent to the terminal device, thereby triggering the terminal device to display a prompt window including the prompt message indicating that the pop-up operation may be incorrect and the predicted operation, which can effectively reduce the error rate of the pop-up operation.

[0050] Example 5 Figure 5 This is a flowchart of the fifth embodiment of the method for reducing the error rate of pop-up window operations according to the present invention. Based on the above embodiment, after sending the prompt information that the pop-up window operation may have an error to the terminal device, the method further includes: S53. Receive information sent by the terminal device that is used to confirm the execution of the pop-up operation in the prompt window; S54. Send a solution to the erroneous operation to the terminal device to trigger the terminal device to display the solution to the erroneous operation in a floating window.

[0051] In this embodiment, the floating window can specifically collapse into a floating ball. When the user clicks the floating ball, it expands to display a floating window interface containing the solutions to the misoperation, thereby reminding the user how to resolve the issue after a misoperation. Furthermore, the color of the floating window can be customized to serve as a prompt.

[0052] In this embodiment of the application, the solution to the erroneous operation may include the method and specific location for modifying the previously executed pop-up operation.

[0053] In this embodiment, after sending a message indicating a possible error in the pop-up operation to the terminal device, if the terminal device receives a message confirming the execution of the pop-up operation, a solution to the error is sent to the terminal device in response to the received message confirming the execution of the pop-up operation. This triggers the terminal device to display the solution in a floating window, allowing the user to easily view the solution and correct the error. This saves the user time in finding a solution and improves the user experience.

[0054] In this embodiment of the application, for example, the pop-up operation is to prohibit the installation of other applications within the application, and the prediction operation is to allow the installation of other applications within the application. If it is determined that the prediction operation and the pop-up operation are inconsistent, a prompt message indicating that the pop-up operation may be incorrect is sent to the terminal device. In response to the terminal device sending information that confirms the execution of the pop-up operation (i.e., prohibiting the installation of other applications within the application) in the prompt window, a solution for the misoperation is sent to the terminal device. This triggers the terminal device to display a solution for the misoperation in the system settings or application permission settings (whether to prohibit the installation of other applications) in a floating window, allowing for quick modification to allow the installation of other applications within the application.

[0055] In this embodiment of the application, sending the prompt message to the terminal device further includes: Send a solution to the erroneous operation to the terminal device to trigger the terminal device to display the solution in a floating window.

[0056] In this embodiment of the application, if the prediction operation is inconsistent with the pop-up operation, the error message indicating that the pop-up operation may be incorrect may not be sent to the terminal device. Instead, the solution to the error operation may be sent directly to the terminal device to trigger the terminal device to display the solution to the error operation in a floating window. In this way, the user can directly understand the solution to the error operation without having to operate the prompt window again.

[0057] The beneficial effect of this embodiment is that by sending a solution to the erroneous operation to the terminal device, the terminal device is triggered to display the solution in a floating window, which makes it easier for the user to modify the erroneous operation based on the solution and improves the user experience.

[0058] Example 6 Figure 6 This is a flowchart of the sixth embodiment of the method for reducing the error rate of pop-up window operations according to the present invention. The method for reducing the error rate of pop-up window operations is applied to a server, and the method may include: S1. Based on a preset artificial intelligence algorithm, learn the relationship between the operation use cases, application functions and pop-up functions of the target application to construct the pop-up operation features of the target application; S2. Based on the historical pop-up operation data of multiple sample users, construct a classification rule for user operation groups. The classification rule is used to divide the multiple sample users into multiple user operation groups. S3. Based on the classification rules and the historical pop-up operation data of the terminal device user, determine the target user operation group corresponding to the terminal device user from the multiple user operation groups; S6. Receive a pop-up operation sent by the terminal device that acts on the first pop-up window of the target application, and predict the probability of erroneous operation of the pop-up operation based on the target user operation group and the pop-up operation characteristics of the target application. S7. If the probability of the erroneous operation is greater than the preset probability, send the prompt message to the terminal device.

[0059] In this embodiment, the prompt information may include a predicted operation determined by predicting the operation of the first pop-up window. For example, if the predicted operation is to upgrade an application, the prompt information may indicate that the user intends to upgrade the application, and if the user clicks incorrectly, they will need to find a specific entry point to restore the upgrade function. It is understood that the prompt information may also include other information, which is not limited here. The preset probability may be pre-set, such as 80%, 90%, etc., and is not limited here. The predicted operation may be a pop-up operation predicted for the target user corresponding to the target user operation group.

[0060] In this embodiment, a pop-up operation that acts on the first pop-up window of the target application is received from the terminal device. Based on the determined target user operation group corresponding to the terminal device user and the pop-up operation characteristics of the target application, the probability of incorrect operation of the pop-up operation is predicted. If the probability of incorrect operation is greater than a preset probability, the prompt information is sent to the terminal device so that the terminal device can subsequently display the prompt information in a prompt window above the first window, which can reduce the probability of the user clicking the pop-up window incorrectly.

[0061] In this embodiment of the application, taking the determined target user operation group as the error operation group as an example, the pop-up operation characteristics of the target application can be used to determine the options currently present in the pop-up and the results corresponding to each option. Based on the error operation group, it can be determined that the terminal device user often makes mistakes in operating a certain option in the pop-up. In this way, it can be predicted that the probability of making a mistake in operating a certain option is greater than a preset probability. The prompt information is then sent to the terminal device to remind the terminal device user, which can improve the user experience.

[0062] In this embodiment of the application, if the probability of the erroneous operation is less than or equal to a preset probability, no prompt information will be generated, that is, the step of sending the prompt information to the terminal device will not be executed.

[0063] The beneficial effect of this embodiment is that by predicting the probability of erroneous operation of the pop-up window, and sending the prompt information to the terminal device when the probability of erroneous operation is greater than a preset probability, the terminal device can subsequently display the prompt information in a prompt window above the first window, thereby reducing the probability of user errors in pop-up window operations.

[0064] Example 7 Based on the above embodiments, this application also provides an electronic device for reducing the error rate of pop-up window operations. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the method for reducing the error rate of pop-up window operations as described in any of the above claims.

[0065] It should be noted that the above-described electronic device embodiments and method embodiments belong to the same concept. For details of their implementation process, please refer to the method embodiments. Furthermore, the technical features in the method embodiments are all applicable to the electronic device embodiments, and will not be repeated here.

[0066] Example 8 Based on the above embodiments, the present invention also proposes a computer-readable storage medium storing a program for reducing the error rate of pop-up window operations. When the program for reducing the error rate of pop-up window operations is executed by a processor, it implements the steps of the method for reducing the error rate of pop-up window operations as described in any of the above claims.

[0067] It should be noted that the above-described medium embodiments and method embodiments belong to the same concept. The specific implementation process can be found in the method embodiments, and the technical features in the method embodiments are also applicable to the medium embodiments, which will not be repeated here.

[0068] The method, electronic device, and computer-readable storage medium for reducing pop-up operation error rates according to embodiments of this application learn the relationship between operation use cases, application functions, and pop-up functions of a target application based on a preset artificial intelligence algorithm. Based on historical pop-up operation data from multiple sample users, a classification rule for user operation groups is constructed. Then, based on the classification rule and historical pop-up operation data of terminal device users, a target user operation group corresponding to the terminal device user is determined. Furthermore, based on the target user operation group and the pop-up operation characteristics of the target application, an operation prediction is performed on the first pop-up acting on the target application. If the predicted operation is inconsistent with the actual pop-up operation, a prompt message is sent to the terminal device to trigger the display of a prompt window, thereby reducing the pop-up operation error rate. Simultaneously, in response to the information sent by the terminal device confirming the execution of the pop-up operation in the prompt window, a solution to the error is sent to the terminal device, triggering the terminal device to display the solution as a floating window, thus improving the user experience.

[0069] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0070] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0071] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0072] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims. All of these forms are within the protection scope of this application.

Claims

1. A method for reducing the error rate of pop-up operation, applied to a server, comprising: The method comprises: ​ learning, based on a preset artificial intelligence algorithm, a correlation between an operation case of a target application, an application function, and a pop-up window function, to construct a pop-up window operation feature of the target application; constructing, based on historical pop-up window operation data of a plurality of sample users, a classification rule of a user operation group, the classification rule being used to divide the plurality of sample users into a plurality of user operation groups; determining, based on the classification rule and historical pop-up window operation data of a terminal device user, a target user operation group corresponding to the terminal device user from the plurality of user operation groups; receiving a pop-up window operation of a first pop-up window of the target application sent by the terminal device, performing operation prediction on the first pop-up window based on the target user operation group and the pop-up window operation feature of the target application, and determining a predicted operation; if the predicted operation is inconsistent with the pop-up window operation, sending a prompt information to the terminal device. 2.The method of claim 1, wherein, The method of constructing, based on historical pop-up window operation data of a plurality of sample users, a classification rule of a user operation group comprises: performing feature identification on the historical pop-up window operation data of the plurality of sample users by using a KMeans clustering algorithm to obtain feature identification data; performing clustering on the feature identification data to construct the classification rule of the user operation group, wherein the mapping relationship between a sample user and a user operation group is one-to-one. 3.The method of claim 2, wherein, The user operation group comprises a positive operation group, a negative operation group, a hesitant operation group, and an error operation group, and the method of determining, based on the classification rule and historical pop-up window operation data of a terminal device user, a target user operation group corresponding to the terminal device user from the plurality of user operation groups comprises: obtaining historical pop-up window operation data of the terminal device user; determining, based on the classification rule and the historical pop-up window operation data, the target user operation group corresponding to the terminal device user from the positive operation group, the negative operation group, the hesitant operation group, and the error operation group. 4.The method of claim 1, wherein, After the method of receiving the pop-up window operation of the first pop-up window of the target application sent by the terminal device, the method further comprises: predicting, based on the target user operation group and the pop-up window operation feature of the target application, an error operation probability of the pop-up window operation; if the error operation probability is greater than a preset probability, sending the prompt information to the terminal device. 5.The method of claim 4, wherein, The prompt information comprises a predicted operation determined by performing operation prediction on the first pop-up window.

6. The method of claim 1, wherein the pop-up window is displayed on a screen of the electronic device. The method of sending, if the predicted operation is inconsistent with the pop-up window operation, a prompt information to the terminal device comprises: comparing the pop-up window operation with the predicted operation; if the predicted operation is inconsistent with the pop-up window operation, sending a prompt information that the pop-up window operation may be wrong to the terminal device to trigger the terminal device to display a prompt window, wherein the prompt window comprises the prompt information that the pop-up window operation may be wrong and the predicted operation, and the prompt window is displayed above the first pop-up window.

7. The method of claim 6, wherein the pop-up window is displayed in a form of a pop-up window, and the pop-up window is displayed in a form of a balloon window. After the method of sending the prompt information that the pop-up window operation may be wrong to the terminal device, the method further comprises: receiving information sent by the terminal device, the information indicating that the terminal device confirms to perform the pop-up window operation on the prompt window; sending a misoperation solution to the terminal device to trigger the terminal device to display the misoperation solution in a floating window manner.

8. The method of claim 1, wherein the pop-up window is displayed on a screen of the electronic device. The method further includes: sending a misoperation solution to the terminal device to trigger the terminal device to display the misoperation solution in a floating window manner.

9. An electronic device, comprising: The method further includes: a memory, a processor, and a computer program stored in the memory and running on the processor, the computer program being executed by the processor to implement the steps of the method for reducing the error rate of the pop-up window operation according to any one of claims 1 to 8.

10. A computer storage medium, characterized in that, The computer storage medium stores a program for reducing the error rate of the pop-up window operation, and the program for reducing the error rate of the pop-up window operation is executed by the processor to implement the steps of the method for reducing the error rate of the pop-up window operation according to any one of claims 1 to 8.

Images