Advertisement processing method, device and equipment based on Windows operating system and medium

Abstract

The invention relates to the technical field of advertisement processing, and provides an advertisement processing method and device based on a Windows operating system, equipment and a medium, and the method comprises the steps: obtaining a notification message of a notification center of the Windows operating system; identifying the notification message, and judging whether the notification message is an advertisement or not according to an identification result; and in response to the judgment that the notification message is an advertisement, executing a corresponding advertisement processing operation. Through the technical scheme of the invention, the advertisement information displayed through the notification center can be accurately identified, frequent interference of a user is avoided, the intelligence level of advertisement interception is improved, the user can obtain cleaner and more comfortable notification experience, and meanwhile, the user is protected from interference of abusing the notification center by advertisement software.

Description

Technical Field

[0001] This application relates to the field of advertising processing technologies, and particularly to an advertising processing method, device, equipment, and medium based on the Windows operating system.

Background Art

[0002] With the development of computer operating systems, the Windows system has gradually introduced the "Notification Center" function to display various system messages and application notifications for users. Especially in Windows 10 and higher versions, the Notification Center provides a centralized location for displaying reminders and notifications from the system and applications. The Notification Center uses the ToastNotification API to show concise messages to users, mainly for non-intrusive information delivery, such as application update reminders, system messages, calendar events, etc.

[0003] However, with the continuous evolution of advertising forms, some applications have started to use the Notification Center to display advertisements or promotional information. These advertisements are delivered through the Notification Center. Although they look similar to standard application notifications in appearance, their purpose is to promote commercial content rather than provide actual service information. Therefore, this practice not only increases user interference but may also bypass existing ad-blocking tools because these advertisements do not use the traditional pop-up form and cannot be effectively recognized and processed by existing blocking tools.

[0004] Currently, the Windows system only provides functions for processing and closing notifications at the process level. Specifically, users can manually close notifications or set not to display notifications from certain applications, but the system itself does not provide a mechanism for third-party programs to directly access the content and text information of notifications. This has led to several problems:

[0005] 1) Advertising abuse: Some application programs display advertisements through the Notification Center instead of traditional pop-up advertisements. Since these advertisements are similar in appearance to normal system notifications, existing ad-blocking tools are difficult to detect and intercept these notifications, resulting in users frequently receiving advertising interference.

[0006] 2) Unable to identify notification content: The Windows operating system does not open an interface for third-party programs to directly obtain the detailed text information of notifications, which makes it impossible for external programs to determine whether a notification is an advertisement, resulting in ineffective identification and interception of advertisements.

[0007] 3) User experience is damaged: Due to the lack of an effective advertisement recognition mechanism, users often receive unnecessary advertisement pushes, affecting the normal notification experience and operation efficiency, and increasing the user's operation burden and mental burden.

[0008] 4) Lack of intelligent interception: Existing solutions usually rely on static advertisement phrase matching or only handle standard advertisement pop-ups, unable to dynamically identify advertisements shown through the notification center and unable to make intelligent responses based on the content of the notifications.

Summary of the Invention

[0009] Embodiments of the present application provide an advertisement processing method, apparatus, device, and medium based on the Windows operating system, aiming to solve the technical problems existing in the related art.

[0010] In a first aspect, embodiments of the present application provide an advertisement processing method based on the Windows operating system, including:

[0011] Obtain the notification message of the notification center of the Windows operating system;

[0012] Identify the notification message, and determine whether the notification message is an advertisement according to the identification result;

[0013] In response to determining that the notification message is an advertisement, perform the corresponding advertisement processing operation.

[0014] In one embodiment, optionally, in response to determining that the notification message is an advertisement, performing the corresponding advertisement processing operation includes:

[0015] Output an advertisement closing prompt message according to the first advertisement processing setting to prompt the user whether to close the advertisement;

[0016] Receive the advertisement closing instruction input by the user according to the advertisement closing prompt message;

[0017] Close the display page corresponding to the notification message according to the advertisement marking instruction; or

[0018] Directly close the display page corresponding to the notification message according to the second advertisement processing setting.

[0019] In one embodiment, optionally, identifying the notification message and determining whether the notification message is an advertisement according to the identification result includes:

[0020] Output the notification message to the corresponding user of the Windows operating system;

[0021] Receive the advertisement marking operation performed by the user on the notification message, determine that the notification message is an advertisement according to the advertisement marking operation, mark the notification message as an advertisement, and record the source process information and path information of the notification message.

[0022] In one embodiment, optionally, obtaining the notification messages of the notification center of the Windows operating system includes:

[0023] Obtaining the notification messages of the notification center of the Windows operating system by injecting an API interface;

[0024] Identifying the notification messages, and judging whether the notification messages are advertisements according to the identification results, including:

[0025] Judging whether the message content of the notification messages can be extracted by the injected API interface;

[0026] In response to the message content of the notification messages being extractable by the injected API interface, extracting the message content;

[0027] Judging whether the notification messages are advertisements according to the message content, the source process information and the path information of the notification messages;

[0028] In response to the message content of the notification messages not being extractable by the injected API interface, performing OCR recognition on the notification messages;

[0029] Extracting the message content of the notification messages according to the OCR recognition results;

[0030] Judging whether the notification messages are advertisements according to the message content, the source process information and the path information of the notification messages.

[0031] In one embodiment, optionally, judging whether the notification messages are advertisements according to the message content, the source process information and the path information of the notification messages includes:

[0032] In response to the message content, the source process information or the path information of the notification messages meeting a preset condition, judging that the notification messages are advertisements, where the preset condition includes at least one of the following:

[0033] The message content contains a preset keyword;

[0034] The message content contains a preset image feature;

[0035] The occurrence times of the notification messages with the same source process information or path information are greater than a preset number;

[0036] The occurrence frequency of the notification messages with the same source process information or path information is greater than a preset frequency.

[0037] In one embodiment, optionally, the method further includes:

[0038] Determine and update the weight value corresponding to each notification message according to the advertisement recognition method corresponding to the notification message;

[0039] Calculate the malicious index value corresponding to each notification message according to the weight value;

[0040] Count the advertisement marking times and advertisement recognition times corresponding to each notification message within a preset time period;

[0041] Generate a statistical report according to the advertisement marking times, advertisement recognition times, source process information, path information, whether it is an advertisement, and malicious index value corresponding to each notification message;

[0042] Output the statistical report.

[0043] In one embodiment, optionally, determining and updating the weight value corresponding to each notification message according to the advertisement recognition method corresponding to the notification message includes:

[0044] When the advertisement recognition method corresponding to the notification message is the injection API interface recognition method, determine the frequency influence weight, the first confidence value, the first user feedback weight factor, and the user feedback value corresponding to the notification message;

[0045] Calculate the first weight value corresponding to the notification message by using a first calculation formula according to the frequency influence weight, the first confidence value, the first user feedback weight factor, and the user feedback value corresponding to the notification message;

[0046] When the advertisement recognition method corresponding to the notification message is the OCR recognition method, determine the frequency influence weight, the second confidence value, the second user feedback weight factor, and the user feedback value corresponding to the notification message;

[0047] Calculate the second weight value corresponding to the notification message by using a second calculation formula according to the frequency influence weight, the second confidence value, the second user feedback weight factor, and the user feedback value corresponding to the notification message;

[0048] When the advertisement recognition method corresponding to the notification message is the user marking recognition method, determine the third confidence value and the third user feedback weight factor corresponding to the notification message;

[0049] Calculate the third weight value corresponding to the notification message by using a third calculation formula according to the third confidence value and the third user feedback weight factor corresponding to the notification message.

[0050] In a second aspect, an advertisement processing device based on the Windows operating system provided by an embodiment of the present application includes:

[0051] An acquisition module, configured to acquire notification messages of the notification center of the Windows operating system;

[0052] An identification module, configured to identify the notification messages, and determine whether the notification messages are advertisements according to the identification results;

[0053] An execution module, configured to perform corresponding advertisement processing operations in response to determining that the notification messages are advertisements.

[0054] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned advertisement processing method based on the Windows operating system are implemented.

[0055] In a fourth aspect, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned advertisement processing method based on the Windows operating system are implemented.

[0056] In the solutions implemented by the above-mentioned advertisement processing method, device, device and medium based on the Windows operating system, notification messages of the notification center of the Windows operating system are acquired; the notification messages are identified, and it is determined whether the notification messages are advertisements according to the identification results; in response to determining that the notification messages are advertisements, corresponding advertisement processing operations are performed. Through the technical solution of the present invention, a method for identifying, detecting and intercepting advertisement notifications through the Windows notification center is provided, which can accurately identify advertisement information displayed through the notification center, avoid users from being frequently disturbed, and improve the intelligent level of advertisement interception. Through this method, users can obtain a cleaner and more comfortable notification experience, and at the same time protect users from the interference of advertisement software abusing the notification center.

Description of the Drawings

[0057] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained according to these drawings without creative efforts.

[0058] Figure 1 A schematic flowchart of an advertisement processing method based on the Windows operating system according to an embodiment of the present application is shown.

[0059] Figure 2A A schematic flowchart of step S102 in an advertisement processing method based on the Windows operating system according to an embodiment of the present application is shown.

[0060] Figure 2B Shows a page screenshot of a notification message according to an embodiment of the present application.

[0061] Figure 3 Shows a schematic flowchart of an advertisement processing method based on the Windows operating system according to another embodiment of the present application.

[0062] Figure 4 Shows a page screenshot of a report corresponding to a notification message according to an embodiment of the present application.

[0063] Figure 5 Shows a block diagram of an advertisement processing apparatus based on the Windows operating system according to an embodiment of the present application.

[0064] Figure 6 Shows a block diagram of a computer device according to an embodiment of the present application.

Detailed implementation manners

[0065] For a better understanding of the technical solution of the present application, the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0066] It should be clear that the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts belong to the scope of protection of the present application.

[0067] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "the" and "said" used in the embodiments of the present application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0068] The following will describe in detail some embodiments of the present application with reference to the accompanying drawings. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0069] Please refer to Figure 1 , Figure 1 Shows a schematic flowchart of an advertisement processing method based on the Windows operating system according to an embodiment of the present application.

[0070] As Figure 1 shown, for an advertisement processing method based on the Windows operating system according to an embodiment of the present application, the process includes:

[0071] Step S101, obtain the notification messages in the notification center of the Windows operating system;

[0072] In one embodiment, optionally, obtaining the notification message of the Windows operating system's notification center includes:

[0073] Obtaining the notification message of the Windows operating system's notification center through injecting an API interface.

[0074] In this embodiment, by injecting and monitoring specific system APIs, it is possible to capture the message trigger event of the notification center in real time, and obtain the process to which the notification belongs and its path information. This technology can break the traditional access restrictions of the notification center, achieve comprehensive monitoring of notification content, and help users accurately identify which notifications belong to advertisements or other bad information. Compared with the prior art, the present invention solves the problem that the traditional method cannot obtain the specific text content of the notification through precise control at the program level, and greatly improves the accuracy of advertisement recognition.

[0075] Step S102, identifying the notification message, and judging whether the notification message is an advertisement according to the identification result;

[0076] As Figure 2A shown, in one embodiment, optionally, step S102 includes:

[0077] Step S201, judging whether the injected API interface can extract the message content of the notification message;

[0078] Step S202, in response to the injected API interface being able to extract the message content of the notification message, extracting the message content;

[0079] Step S203, judging whether the notification message is an advertisement according to the message content, the source process information and the path information of the notification message;

[0080] In this embodiment, the system captures the message trigger event of the notification center in real time by injecting and monitoring specific system APIs (such as Windows ToastNotification API and background services). Identify the source process of the notification and obtain its path information, extract the title and content summary of the notification, and provide basic data support.

[0081] Step S204, in response to the injected API interface being unable to extract the message content of the notification message, performing OCR recognition on the notification message;

[0082] In this step, when the notification content is presented in the form of an image or other non-textual means (such as an advertisement image), the system uses OCR technology to scan the image and extract the text content. OCR converts the image text into processable data, enhancing the ability to detect advertisement content. In a complex image background, the accuracy is improved by combining multiple recognition results.

[0083] Step S205, extract the message content of the notification message according to the OCR recognition result;

[0084] Step S206, determine whether the notification message is an advertisement according to the message content, the source process information and the path information of the notification message.

[0085] In one embodiment, optionally, step S206 includes:

[0086] In response to the message content, the source process information or the path information of the notification message satisfying a preset condition, determine that the notification message is an advertisement, where the preset condition includes at least one of the following:

[0087] The message content contains a preset keyword;

[0088] The message content contains a preset image feature;

[0089] The occurrence times of notification messages with the same source process information or path information are greater than a preset number;

[0090] The occurrence frequency of notification messages with the same source process information or path information is greater than a preset frequency.

[0091] In this step, it is possible to determine whether a notification message is an advertisement by determining whether the message content, the source process information or the path information of the notification message satisfies a preset condition. For example, it is possible to analyze whether the notification content matches the keyword, and it is also possible to determine whether the notification pop-up frequency exceeds a threshold. It is also possible to determine whether the text contains advertisement vocabulary or promotional information. Whether the notification style has repetitive, extreme or promotional image features. Of course, it is also possible to perform advertisement determination through a machine learning model combined with the user feedback recognition mode. Thus, the accuracy of the determination is ensured.

[0092] In this embodiment, the introduction of OCR (Optical Character Recognition) technology can recognize the text content in the image displayed in the notification center, further improving the accuracy of notification content inspection. Even if the advertisement content is displayed in the form of an image, the OCR technology can help extract the text information therein, realizing a comprehensive analysis of the notification. Compared with the prior art, the present invention can detect advertisement content displayed in the form of an image or a hybrid manner, avoiding the limitations of traditional text recognition methods and improving the accuracy of advertisement interception.

[0093] In one embodiment, optionally, step S102 includes:

[0094] Output the notification message to the user corresponding to the Windows operating system;

[0095] Receive the advertisement marking operation performed by the user on the notification message, determine that the notification message is an advertisement according to the advertisement marking operation, perform advertisement marking on the notification message, and record the source process information and path information of the notification message.

[0096] In this embodiment, as Figure 2B shown, after the notification pops up, ask the user whether the notification is an advertisement and provide an option to close it. If the user confirms that the notification is an advertisement, the present invention ensures that the advertisement can be effectively closed by simulating a click or sending a close message. At the same time, the advertisement process will be marked, and a weight value can be assigned to the process according to the user feedback, so as to accurately identify and process similar advertisement processes subsequently. Through this intelligent feedback mechanism, the present invention can continuously optimize the advertisement recognition algorithm, improve the success rate of advertisement interception, and improve the user experience.

[0097] Step S103, in response to determining that the notification message is an advertisement, perform corresponding advertisement processing operations.

[0098] In one embodiment, optionally, step S103 includes:

[0099] Output an advertisement closing prompt message according to the first advertisement processing setting to prompt the user whether to close the advertisement;

[0100] Receive the advertisement closing instruction input by the user according to the advertisement closing prompt message;

[0101] Close the display page corresponding to the notification message according to the advertisement marking instruction.

[0102] In this embodiment, if the user confirms that the notification is an advertisement, the present invention ensures that the advertisement can be effectively closed by simulating a click or sending a close message.

[0103] Directly close the display page corresponding to the notification message according to the second advertisement processing setting.

[0104] Of course, for the convenience of the user, the user can also make settings in advance. For example, if the user sets to automatically close the notification message when an advertisement is recognized, in this way, the display page corresponding to the notification message can be directly closed without prompting the user.

[0105] As Figure 3 shown, in one embodiment, optionally, the method further includes:

[0106] Step S301: Determine and update the weight value corresponding to each notification message according to the advertisement recognition method corresponding to the notification message.

[0107] In one embodiment, optionally, step S301 includes:

[0108] When the advertisement recognition method corresponding to the notification message is the injection API interface recognition method, determine the frequency influence weight, the first confidence value, the first user feedback weight factor, and the user feedback value corresponding to the notification message.

[0109] According to the frequency influence weight, the first confidence value, the first user feedback weight factor, and the user feedback value corresponding to the notification message, calculate the first weight value W1 corresponding to the notification message by using the first calculation formula.

[0110] The first calculation formula is:

[0111] W1 = F(N) × (1 + αU)

[0112] Wherein, F(N) represents the notification frequency influence weight; α represents the first user feedback weight factor; U represents the user marked feedback value. Among them, the first confidence level is 1. Of course, it can also be other values.

[0113] When the advertisement recognition method corresponding to the notification message is the OCR recognition method, determine the frequency influence weight, the second confidence value, the second user feedback weight factor, and the user feedback value corresponding to the notification message.

[0114] According to the frequency influence weight, the second confidence value, the second user feedback weight factor, and the user feedback value corresponding to the notification message, calculate the second weight value W2 corresponding to the notification message by using the second calculation formula.

[0115] The second calculation formula is:

[0116] W2 = F(N) × (0.7 + βU)

[0117] Wherein, F(N) represents the notification frequency influence weight; β represents the second user feedback weight factor; U represents the user marked feedback value. Among them, the second confidence level is 0.7. Of course, it can also be other values.

[0118] When the advertisement recognition method corresponding to the notification message is the user marking recognition method, determine the third confidence value and the third user feedback weight factor corresponding to the notification message.

[0119] According to the third confidence value and the third user feedback weight factor corresponding to the notification message, calculate the third weight value W3 corresponding to the notification message by using the third calculation formula.

[0120] The third calculation formula is as follows;

[0121] W3 = γU

[0122] Where γ represents the third user feedback weight factor, and U represents the user marked feedback value.

[0123] Step S302: Calculate the malicious index value corresponding to each notification message according to the weight value;

[0124] Normalization processing of the malicious index:

[0125] Normalization processing for different processes:

[0126] Formula:

[0127]

[0128] Where W represents the weight value calculated according to its respective formula; Wmax represents the theoretical maximum weight of the corresponding source (dynamically calculated or defined according to the actual situation).

[0129] Example calculation:

[0130] Assume the following parameters:

[0131] F(N) = 10, the notification frequency weight is fixed;

[0132] Umax = 1.0, the maximum user marked feedback value;

[0133] αmax = 0.5, the first user feedback weight factor;

[0134] βmax = 0.4, the second user feedback weight factor;

[0135] γmax = 0.6, the third user feedback weight factor.

[0136] Calculate the maximum weight:

[0137] API data: w = 15

[0138] OCR data: W = 11

[0139] User feedback: W = 0.6

[0140] Normalization example (assuming the actual feedback value U = 0.8):

[0141] 1. API data:

[0142] w = 10 * (1 + 0.5 * 0.8) = 14

[0143] After normalization: 14 / 15 * 100 = 93.3

[0144] 2. OCR data:

[0145] w = 10 * (0.7 + 0.4 * 0.8) = 10.2

[0146] After normalization: 10.2 / 11 * 100 = 92.7

[0147] 3. User feedback

[0148] w = 0.6 * 0.8 = 0.48

[0149] After normalization: 0.48 / 0.6 = 80

[0150] For different source data of the same process, weighted fusion is adopted:

[0151] Formula:

[0152]

[0153] Step S303, count the number of advertisement marking times and advertisement recognition times corresponding to each notification message within a preset time period;

[0154] Step S304, generate a statistical report according to the advertisement marking times, advertisement recognition times, source process information, path information, whether it is an advertisement, and malicious index value corresponding to each notification message;

[0155] Step S305, output the statistical report.

[0156] In this embodiment, user feedback and advertisement recognition data are collected to generate a statistical report to provide an advertisement blocking reference for users. For example, as Figure 4 shown, the weight of the advertisement can be displayed in the final report using concepts such as the malicious index. In this way, it is provided for other users to refer to and helps them avoid similar advertisement interferences. Of course, the advertisement can also be blocked according to the malicious index, etc. For example, if the malicious index of a certain notification message is higher than the threshold, then directly block or close the notification message.

[0157] Through the above technical solution of the present invention, obtain the notification messages of the notification center of the Windows operating system; identify the notification messages, and determine whether the notification messages are advertisements according to the identification results; in response to determining that the notification messages are advertisements, perform corresponding advertisement processing operations. Through the technical solution of the present invention, a method for identifying, detecting and intercepting advertisement notifications through the Windows notification center is provided, which can accurately identify the advertisement information displayed through the notification center, avoid users being frequently disturbed, and improve the intelligent level of advertisement interception. Through this method, users can obtain a cleaner and more comfortable notification experience, and at the same time protect users from the interference of advertisement software abusing the notification center.

[0158] Figure 5 FIG. shows a block diagram of an advertisement processing apparatus based on the Windows operating system according to an embodiment of the present application.

[0159] As Figure 5 shown, in a second aspect, an embodiment of the present application provides an advertisement processing apparatus 50 based on the Windows operating system, including:

[0160] An obtaining module 51, configured to obtain the notification messages of the notification center of the Windows operating system;

[0161] An identifying module 52, configured to identify the notification messages and determine whether the notification messages are advertisements according to the identification results;

[0162] An executing module 53, configured to perform corresponding advertisement processing operations in response to determining that the notification messages are advertisements.

[0163] In one embodiment, optionally, the executing module includes:

[0164] A prompting unit, configured to output an advertisement closing prompt message according to the first advertisement processing setting to prompt the user whether to close the advertisement;

[0165] A receiving unit, configured to receive the advertisement closing instruction input by the user according to the advertisement closing prompt message;

[0166] A first closing unit, configured to close the display page corresponding to the notification message according to the advertisement marking instruction; or

[0167] A second closing unit, configured to directly close the display page corresponding to the notification message according to the second advertisement processing setting.

[0168] In one embodiment, optionally, the identifying module includes:

[0169] An output unit, configured to output the notification message to the corresponding user of the Windows operating system;

[0170] A marking unit, configured to receive an advertisement marking operation performed by the user on the notification message, determine that the notification message is an advertisement according to the advertisement marking operation, perform advertisement marking on the notification message, and record the source process information and path information of the notification message.

[0171] In one embodiment, optionally, the obtaining module includes:

[0172] A message obtaining unit, configured to obtain the notification message of the notification center of the Windows operating system through an injected API interface;

[0173] The recognition module includes:

[0174] A first judgment unit, configured to judge whether the injected API interface can extract the message content of the notification message;

[0175] A first extraction unit, configured to extract the message content in response to the injected API interface being able to extract the message content of the notification message;

[0176] A second judgment unit, configured to judge whether the notification message is an advertisement according to the message content and the source process information and path information of the notification message;

[0177] An identification unit, configured to perform OCR identification on the notification message in response to the injected API interface being unable to extract the message content of the notification message;

[0178] A second extraction unit, configured to extract the message content of the notification message according to the OCR recognition result;

[0179] A third judgment unit, configured to judge whether the notification message is an advertisement according to the message content and the source process information and path information of the notification message.

[0180] In one embodiment, optionally, the second judgment unit is configured to:

[0181] In response to the message content, the source process information or path information of the notification message satisfying a preset condition, judge that the notification message is an advertisement, where the preset condition includes at least one of the following:

[0182] The message content contains a preset keyword;

[0183] The message content contains a preset image feature;

[0184] The occurrence times of the notification messages with the same source process information or path information are greater than a preset number of times;

[0185] The occurrence frequency of notification messages with the same source process information or path information is greater than a preset frequency.

[0186] In one embodiment, optionally, the device further includes:

[0187] An update module, configured to determine and update the weight value corresponding to each notification message according to the advertisement recognition method corresponding to each notification message;

[0188] A calculation module, configured to calculate the malicious index value corresponding to each notification message according to the weight value;

[0189] A statistics module, configured to count the advertisement marking times and advertisement recognition times corresponding to each notification message within a preset time period;

[0190] A generation module, configured to generate a statistical report according to the advertisement marking times, advertisement recognition times, source process information, path information, whether it is an advertisement, and malicious index value corresponding to each notification message;

[0191] A report output module, configured to output the statistical report.

[0192] In one embodiment, optionally, the update module is configured to:

[0193] When the advertisement recognition method corresponding to the notification message is the injection API interface recognition method, determine the frequency influence weight, the first confidence value, the first user feedback weight factor, and the user feedback value corresponding to the notification message;

[0194] According to the frequency influence weight, the first confidence value, the first user feedback weight factor, and the user feedback value corresponding to the notification message, calculate the first weight value corresponding to the notification message by using a first calculation formula;

[0195] When the advertisement recognition method corresponding to the notification message is the OCR recognition method, determine the frequency influence weight, the second confidence value, the second user feedback weight factor, and the user feedback value corresponding to the notification message;

[0196] According to the frequency influence weight, the second confidence value, the second user feedback weight factor, and the user feedback value corresponding to the notification message, calculate the second weight value corresponding to the notification message by using a second calculation formula;

[0197] When the advertisement recognition method corresponding to the notification message is the user marking recognition method, determine the third confidence value and the third user feedback weight factor corresponding to the notification message;

[0198] According to the third confidence value and the third user feedback weight factor corresponding to the notification message, calculate the third weight value corresponding to the notification message by using a third calculation formula.

[0199] In a third aspect, a computer device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned advertisement processing method based on the Windows operating system are implemented.

[0200] In a fourth aspect, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned advertisement processing method based on the Windows operating system are implemented.

[0201] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described advertisement processing device based on the Windows operating system and each module can refer to the corresponding processes in the foregoing embodiments of the advertisement processing method based on the Windows operating system, and will not be described in detail here.

[0202] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described model training device and each module can refer to the corresponding processes in the foregoing embodiments of the advertisement processing method based on the Windows operating system, and will not be described in detail here.

[0203] The above-mentioned advertisement processing device based on the Windows operating system can be implemented in the form of a computer program, and this computer program can run on a computer device as shown in Figure 5 as shown.

[0204] Figure 6 The block diagram of a computer device according to an embodiment of the present application is shown.

[0205] Referring to Figure 6 , this computer device includes a processor, a memory, and a network interface connected through a system bus. Among them, the memory may include a storage medium and an internal memory.

[0206] The storage medium can store an operating system and a computer program. This computer program includes program instructions, and when the program instructions are executed, the processor can be enabled to execute any one of the advertisement processing methods based on the Windows operating system provided in the embodiments of the present application.

[0207] The processor is used to provide computing and control capabilities to support the operation of the entire computer device.

[0208] The internal memory provides an environment for the operation of a computer program in a storage medium. When the computer program is executed by a processor, the processor can execute any method for analyzing the transmission path of an infectious disease or a method for training a prediction neural network. The storage medium can be non-volatile or volatile.

[0209] This network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art can understand that Figure 6 the structure shown in is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0210] It should be understood that the processor can be a Central Processing Unit (CPU), and the processor can also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0211] In addition, an embodiment of this application provides a computer-readable storage medium storing computer-executable instructions, and the computer-executable instructions are used to execute the following steps:

[0212] Obtain the notification message of the notification center of the Windows operating system;

[0213] Identify the notification message, and judge whether the notification message is an advertisement according to the recognition result;

[0214] In response to judging that the notification message is an advertisement, execute the corresponding advertisement processing operation.

[0215] In one embodiment, optionally, in response to judging that the notification message is an advertisement, executing the corresponding advertisement processing operation includes:

[0216] According to the first advertisement processing setting, output an advertisement closing prompt message to prompt the user whether to close the advertisement;

[0217] Receive the advertisement closing instruction input by the user according to the advertisement closing prompt message;

[0218] According to the advertisement marking instruction, close the display page corresponding to the notification message; or

[0219] According to the second advertisement processing setting, directly close the display page corresponding to the notification message.

[0220] In one embodiment, optionally, identify the notification message, and judge whether the notification message is an advertisement according to the identification result, including:

[0221] Output the notification message to the user corresponding to the Windows operating system;

[0222] Receive the advertisement marking operation performed by the user on the notification message, determine that the notification message is an advertisement according to the advertisement marking operation, mark the notification message as an advertisement, and record the source process information and path information of the notification message.

[0223] In one embodiment, optionally, obtaining the notification message of the notification center of the Windows operating system includes:

[0224] Obtain the notification message of the notification center of the Windows operating system by injecting the API interface;

[0225] Identify the notification message, and judge whether the notification message is an advertisement according to the identification result, including:

[0226] Judge whether the message content of the notification message can be extracted by the injected API interface;

[0227] In response to the injected API interface being able to extract the message content of the notification message, extract the message content;

[0228] Judge whether the notification message is an advertisement according to the message content, the source process information and the path information of the notification message;

[0229] In response to the injected API interface being unable to extract the message content of the notification message, perform OCR recognition on the notification message;

[0230] Extract the message content of the notification message according to the OCR recognition result;

[0231] Judge whether the notification message is an advertisement according to the message content, the source process information and the path information of the notification message.

[0232] In one embodiment, optionally, judging whether the notification message is an advertisement according to the message content, the source process information and the path information of the notification message includes:

[0233] In response to the message content, the source process information or path information of the notification message satisfying a preset condition, it is determined that the notification message is an advertisement, where the preset condition includes at least one of the following:

[0234] The message content contains a preset keyword;

[0235] The message content contains a preset image feature;

[0236] The number of occurrences of notification messages with the same source process information or path information is greater than a preset number;

[0237] The occurrence frequency of notification messages with the same source process information or path information is greater than a preset frequency.

[0238] In one embodiment, optionally, the method further includes:

[0239] Determine and update the weight value corresponding to each notification message according to the advertisement recognition method corresponding to each notification message;

[0240] Calculate the malicious index value corresponding to each notification message according to the weight value;

[0241] Count the advertisement marking times and advertisement recognition times corresponding to each notification message within a preset time period;

[0242] Generate a statistical report according to the advertisement marking times, advertisement recognition times, source process information, path information, whether it is an advertisement, and malicious index value corresponding to each notification message;

[0243] Output the statistical report.

[0244] In one embodiment, optionally, determining and updating the weight value corresponding to each notification message according to the advertisement recognition method corresponding to each notification message includes:

[0245] When the advertisement recognition method corresponding to the notification message is the injection API interface recognition method, determine the frequency influence weight, the first confidence value, the first user feedback weight factor, and the user feedback value corresponding to the notification message;

[0246] Calculate the first weight value corresponding to the notification message by using a first calculation formula according to the frequency influence weight, the first confidence value, the first user feedback weight factor, and the user feedback value corresponding to the notification message;

[0247] When the advertisement recognition method corresponding to the notification message is the OCR recognition method, determine the frequency influence weight, the second confidence value, the second user feedback weight factor, and the user feedback value corresponding to the notification message;

[0248] Calculate the second weight value corresponding to the notification message by using a second calculation formula according to the frequency influence weight, second confidence value, second user feedback weight factor, and user feedback value corresponding to the notification message;

[0249] When the advertisement recognition method corresponding to the notification message is the user marking recognition method, determine the third confidence value and the third user feedback weight factor corresponding to the notification message;

[0250] Calculate the third weight value corresponding to the notification message by using a third calculation formula according to the third confidence value and the third user feedback weight factor corresponding to the notification message.

[0251] It should be noted that for the functions or steps that the above computer-readable storage medium or electronic device can achieve, reference can be made to the relevant descriptions in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0252] It should be understood that the term "and / or" used herein is only a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0253] It should be understood that although terms such as first and second may be used to describe the setting units in the embodiments of the present application, these setting units should not be limited to these terms. These terms are only used to distinguish the setting units from each other. For example, without departing from the scope of the embodiments of the present application, the first setting unit may also be referred to as the second setting unit, and similarly, the second setting unit may also be referred to as the first setting unit.

[0254] Depending on the context, the word "if" as used herein can be interpreted as "when" or "while" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detected (stated condition or event)" can be interpreted as "when determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)".

[0255] In several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0256] In addition, in each embodiment of this application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of a combination of hardware and software functional units.

[0257] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in each embodiment provided in this application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0258] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. An advertisement processing method based on Windows operating system, characterized in that: The method comprises: Obtain a notification message from a notification center of the Windows operating system; Identify the notification message, and determine whether the notification message is an advertisement according to the identification result; In response to determining that the notification message is an advertisement, a corresponding advertisement processing operation is performed.

2. The method according to claim 1, characterized in that In response to determining that the notification message is an advertisement, performing a corresponding advertisement processing operation, including: Outputting advertisement closing prompt information according to the first advertisement processing setting to prompt the user whether to close the advertisement; receiving an advertisement closing instruction input by the user according to the advertisement closing prompt information; According to the advertisement marking instruction, closing the display page corresponding to the notification message; or According to the second advertisement processing setting, the display page corresponding to the notification message is directly closed.

3. The method according to claim 1, characterized in that Identifying the notification message, and determining whether the notification message is an advertisement according to the identification result, including: Outputting the notification message to a user corresponding to the Windows operating system; Receive an advertisement marking operation performed by the user on the notification message, determine that the notification message is an advertisement according to the advertisement marking operation, mark the notification message as an advertisement, and record source process information and path information of the notification message.

4. The method according to claim 1, characterized in that: The obtaining of a notification message from a notification center of the Windows operating system includes: Obtaining notification messages from the notification center of the Windows operating system by injecting an API interface; Identifying the notification message, and determining whether the notification message is an advertisement according to the identification result, including: Determine whether the injection API interface can extract the message content of the notification message; In response to the injection API interface being able to extract message content of the notification message, extracting the message content; Determining whether the notification message is an advertisement according to the message content and the source process information and path information of the notification message; In response to the injection API interface being unable to extract the message content of the notification message, performing OCR recognition on the notification message; Extracting the message content of the notification message according to the OCR recognition result; Whether the notification message is an advertisement is determined according to the message content and the source process information and path information of the notification message.

5. The method according to claim 1, characterized in that Judging whether the notification message is an advertisement according to the message content and the source process information and path information of the notification message includes: In response to the message content, the source process information or the path information of the notification message satisfying a preset condition, determining that the notification message is an advertisement, wherein the preset condition includes at least one of the following: The message content contains preset keywords; The message content includes a preset image feature; The number of occurrences of notification messages with the same source process information or path information is greater than a preset number; The occurrence frequency of notification messages with the same source process information or path information is greater than a preset frequency.

6. The method according to claim 1, characterized in that The method further comprises: Determine and update the weight value corresponding to each notification message according to the advertisement identification method corresponding to each notification message; Calculate the malicious index value corresponding to each notification message according to the weight value; Count the number of advertisement markings and advertisement recognitions corresponding to each notification message within a preset time period; Generate a statistical report based on the number of advertisement markings, the number of advertisement identifications, the source process information, the path information, whether it is an advertisement, and the malicious index value corresponding to each notification message; Output the statistical report.

7. The method according to claim 6, characterized in that According to the advertisement identification method corresponding to each notification message, determine and update the weight value corresponding to each notification message, including: When the advertisement identification method corresponding to the notification message is an injection API interface identification method, determining a frequency influence weight, a first confidence value, a first user feedback weight factor, and a user feedback value corresponding to the notification message; Calculate a first weight value corresponding to the notification message using a first calculation formula according to the frequency influence weight corresponding to the notification message, the first confidence value, the first user feedback weight factor and the user feedback value; When the advertisement recognition method corresponding to the notification message is an OCR recognition method, determining a frequency influence weight, a second confidence value, a second user feedback weight factor, and a user feedback value corresponding to the notification message; Calculate a second weight value corresponding to the notification message using a second calculation formula according to the frequency influence weight corresponding to the notification message, the second confidence value, the second user feedback weight factor and the user feedback value; When the advertisement identification method corresponding to the notification message is a user mark identification method, determining a third confidence value and a third user feedback weight factor corresponding to the notification message; A third weight value corresponding to the notification message is calculated using a third calculation formula according to the third confidence value corresponding to the notification message and a third user feedback weight factor.

8. An advertisement processing device based on Windows operating system, characterized in that: include: An acquisition module, used to acquire notification messages from a notification center of the Windows operating system; an identification module, used to identify the notification message and determine whether the notification message is an advertisement according to the identification result; The execution module is used to execute a corresponding advertisement processing operation in response to determining that the notification message is an advertisement.

9. A computer device, characterized in that: include: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions executable by the at least one processor, wherein the instructions are configured to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Computer executable instructions are stored, and the computer executable instructions are used to execute the method according to any one of claims 1 to 7.

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