Advertisement popup window filtering method and system

Abstract

The invention relates to the technical field of computers, and discloses an advertisement pop-up window filtering method and system, the advertisement pop-up window filtering method is applied to the advertisement pop-up window filtering system, the advertisement pop-up window filtering system comprises a client and a cloud rule background, and the method comprises the steps that when the client detects a new pop-up window, the client sends the new pop-up window to the cloud rule background; preliminarily filtering the new pop-up window according to the pop-up window information, uploading the pop-up window information to a cloud rule background by the client when a preliminary filtering result is that the pop-up window is abnormal, feeding back a cloud rule matching result to the client by the cloud rule background according to the pop-up window information and a preset cloud rule, and filtering the new pop-up window again by the client according to the cloud rule matching result; according to the method, the pop-up window is filtered in a mode of combining local preliminary screening with cloud matching, so that a new advertisement pop-up window can be accurately and timely found, a reasonable processing rule is formulated, and the user experience can be improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method and system for filtering advertisement pop-up windows. Background Art

[0002] With the development of computer technology, computer applications have entered the era of graphical user interfaces and the Internet. Graphical user interfaces free people from abstract interactive commands, lower the threshold for computer use, and thus promote the popularization of computers. The colorful graphical interface also expands the scope of computer applications. The widespread use of the Internet makes information dissemination and sharing more convenient and efficient. The combination of these two technologies has brought about a huge change in the way information is disseminated, and has completely changed the way people obtain information, thus prompting the media to gradually shift positions from traditional media such as television, newspapers, and magazines to disseminate information to users through the Internet. Driven by interests, while disseminating news, knowledge, entertainment and other information through the Internet, a large number of advertisements are also placed on users through the Internet, causing users' screens to be invaded and polluted by a large number of advertisements. The large number of advertisements with a variety of content is very annoying.

[0003] Among the many forms of advertising on computers, pop-up ads cause the most nuisance to users. However, existing pop-up filtering methods cannot accurately and timely identify ad pop-ups, resulting in a poor user experience.

[0004] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of the present invention is to provide a method and system for filtering advertisement pop-up windows, aiming to solve the technical problem that the existing pop-up window filtering method cannot accurately and timely identify advertisement pop-up windows, thereby resulting in poor user experience.

[0006] To achieve the above object, the present invention provides a method for filtering advertisement pop-up windows, the method for filtering advertisement pop-up windows being applied to a filtering system for advertisement pop-up windows, the filtering system for advertisement pop-up windows comprising: a client and a cloud rule background;

[0007] The method for filtering advertisement pop-up windows comprises the following steps:

[0008] When the client detects a new pop-up window, the client preliminarily filters the new pop-up window according to the pop-up window information;

[0009] When the preliminary filtering result is that the pop-up window is abnormal, the client uploads the pop-up window information to the cloud rule backend;

[0010] The cloud rule backend feeds back the cloud rule matching result to the client according to the pop-up window information and the preset cloud rules;

[0011] The client filters the new pop-up window again according to the cloud rule matching result.

[0012] Optionally, when the client detects a new pop-up window, the step of preliminarily filtering the new pop-up window according to pop-up window information includes:

[0013] When the client detects a new pop-up window, it extracts window features from the pop-up window information;

[0014] The client preliminarily filters the new pop-up window according to the window characteristics.

[0015] Optionally, the step of the client filtering the new pop-up window again according to the cloud rule matching result includes:

[0016] The client determines a preset cloud rule that matches successfully according to the cloud rule matching result, wherein the preset cloud rule includes interception, waiting for user confirmation whether to intercept, and ignoring;

[0017] The client again filters the new pop-up window according to the successfully matched preset cloud rule.

[0018] Optionally, the step of the client filtering the new pop-up window again according to the successfully matched preset cloud rule includes:

[0019] The client obtains user preference information corresponding to the new pop-up window;

[0020] The client again filters the new pop-up window according to the user preference information and the successfully matched preset cloud rules.

[0021] Optionally, after the step of filtering the new pop-up window again according to the user preference information and the successfully matched preset cloud rule, the step further includes:

[0022] The client receives a filtering strategy fed back by the user according to the new pop-up window;

[0023] The client modifies the user preference information corresponding to the new pop-up window according to the filtering strategy.

[0024] Optionally, the step of the cloud rule backend feeding back the cloud rule matching result to the client according to the pop-up window information and preset cloud rules includes:

[0025] The cloud rule backend matches the pop-up window information with a pop-up window sample library, and the pop-up window sample library corresponds to a preset cloud rule;

[0026] The cloud rule backend feeds back the cloud rule matching result to the client according to the matching result between the pop-up window information and the pop-up window sample library.

[0027] Optionally, the pop-up window sample in the pop-up window sample library is at least one of a client reporting sample, a user feedback sample, and a sample collected by an operator.

[0028] Optionally, the advertisement pop-up filtering system further includes: a sample collection terminal; and the method further includes:

[0029] When the cloud rule matching result is a matching failure, the cloud rule backend sends the pop-up window information to the sample collection terminal;

[0030] The sample collection terminal feeds back the storage cloud rules to the cloud rule backend according to the pop-up window information;

[0031] The cloud rule backend adjusts the preset cloud rule according to the incoming cloud rule.

[0032] Optionally, when the client detects a new pop-up window, before the step of preliminarily filtering the new pop-up window according to the pop-up window information, the step further includes:

[0033] The client enumerates windows and obtains window information;

[0034] The client detects a new pop-up window according to the window information.

[0035] Optionally, the step of the client detecting a new pop-up window according to the window information includes:

[0036] The client obtains the user's marking information for the window;

[0037] The client detects a new pop-up window according to the window information and the mark information.

[0038] In addition, to achieve the above-mentioned purpose, the present invention also proposes a system for filtering advertisement pop-ups, the system for filtering advertisement pop-ups comprising: a client and a cloud rule background;

[0039] The client is used to preliminarily filter the new pop-up window according to the pop-up window information when a new pop-up window is detected;

[0040] The client is further used to upload the pop-up window information to the cloud rule backend when the preliminary filtering result is that the pop-up window is abnormal;

[0041] The cloud rule backend is used to feed back the cloud rule matching result to the client according to the pop-up information and the preset cloud rules;

[0042] The client is further configured to filter the new pop-up window again according to the cloud rule matching result.

[0043] Optionally, the client is further configured to extract window features from pop-up window information when a new pop-up window is detected;

[0044] The client is also used to preliminarily filter the new pop-up window according to the window characteristics.

[0045] Optionally, the client is further used to determine a preset cloud rule that matches successfully according to the cloud rule matching result, and the preset cloud rule includes interception, waiting for user confirmation whether to intercept, and ignoring;

[0046] The client is further configured to filter the new pop-up window again according to the successfully matched preset cloud rule.

[0047] Optionally, the client is further used to obtain user preference information corresponding to the new pop-up window;

[0048] The client is further configured to filter the new pop-up window again according to the user preference information and the successfully matched preset cloud rules.

[0049] Optionally, the client is further used to receive a filtering strategy fed back by the user according to the new pop-up window;

[0050] The client is further used to modify the user preference information corresponding to the new pop-up window according to the filtering strategy.

[0051] Optionally, the cloud rule backend is further used to match the pop-up window information with a pop-up window sample library, and the pop-up window sample library corresponds to a preset cloud rule;

[0052] The cloud rule backend is also used to feed back the cloud rule matching result to the client according to the matching result between the pop-up window information and the pop-up window sample library.

[0053] Optionally, the pop-up window sample in the pop-up window sample library is at least one of a client reporting sample, a user feedback sample, and a sample collected by an operator.

[0054] Optionally, the advertisement pop-up filtering system further includes: a sample collection terminal;

[0055] The cloud rule backend is further used to send the pop-up window information to the sample collection terminal when the cloud rule matching result is a matching failure;

[0056] The sample collection terminal is used to feed back the storage cloud rules to the cloud rule backend according to the pop-up window information;

[0057] The cloud rule background is also used to adjust the preset cloud rules according to the incoming cloud rules.

[0058] Optionally, the client is further used to enumerate windows and obtain window information;

[0059] The client is also used to detect a new pop-up window according to the window information.

[0060] Optionally, the client is further used to obtain user marking information for the window;

[0061] The client is further used to detect a new pop-up window according to the window information and the mark information.

[0062] In the present invention, a method for filtering advertisement pop-ups is disclosed and applied to a filtering system for advertisement pop-ups. The filtering system for advertisement pop-ups includes: a client and a cloud rule background. When a new pop-up is detected, the client preliminarily filters the new pop-up according to pop-up information. When the preliminary filtering result of the client is that the pop-up is abnormal, the pop-up information is uploaded to the cloud rule background. The cloud rule background feeds back the cloud rule matching result to the client according to the pop-up information and preset cloud rules. The client filters the new pop-up again according to the cloud rule matching result. Since the present invention performs pop-up filtering by combining local initial screening with cloud matching, it is possible to accurately and timely discover new advertisement pop-ups, and formulate reasonable processing rules, thereby improving user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 This is a flow chart of a first embodiment of a method for filtering advertisement pop-up windows of the present invention;

[0064] Figure 2 This is a flow chart of a second embodiment of a method for filtering advertisement pop-up windows of the present invention;

[0065] Figure 3 It is a flowchart of a third embodiment of a method for filtering advertisement pop-up windows of the present invention;

[0066] Figure 4 This is a device interaction diagram of the filtering system for advertisement pop-up windows of the present invention;

[0067] Figure 5 This is a structural block diagram of a first embodiment of a filtering system for advertisement pop-up windows of the present invention;

[0068] Figure 6 This is a structural block diagram of a third embodiment of the system for filtering pop-up advertisements of the present invention.

[0069] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0070] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0071] Reference Figure 1 , Figure 1 The flowchart of the first embodiment of the method for filtering advertisement pop-ups of the present invention is provided. The first embodiment of the method for filtering advertisement pop-ups of the present invention is provided.

[0072] In a first embodiment, the method for filtering advertisement pop-ups is applied to a system for filtering advertisement pop-ups, and the system for filtering advertisement pop-ups includes: a client and a cloud rule backend;

[0073] The method for filtering advertisement pop-up windows comprises the following steps:

[0074] Step S10: When the client detects a new pop-up window, it preliminarily filters the new pop-up window according to the pop-up window information.

[0075] It should be noted that the client may be pre-installed on the user terminal, wherein the client may be a program corresponding to the cloud rule background and providing local services to the user.

[0076] The cloud rule backend can be a server connected to the Internet for storing and matching cloud rules. In a specific implementation, in order to meet the needs of massive storage and computing, the cloud rule backend is generally a cluster composed of multiple high-performance servers.

[0077] It is understandable that when a new pop-up window is detected, preliminarily filtering the new pop-up window according to the pop-up window information may be to extract window features from the pop-up window information, and preliminarily filtering the new pop-up window according to the window features.

[0078] It should be noted that the window characteristics may include window position, window size, window title, window class name, process file signature, application icon and other characteristics, which are not limited in this embodiment.

[0079] It should be understood that the client can initially filter the new pop-up window according to the window characteristics to detect whether the new pop-up window is a suspected advertising pop-up window. If so, the initial filtering result is that the pop-up window is abnormal; if not, the initial filtering result is that the pop-up window is normal.

[0080] Step S20: When the preliminary filtering result is that the pop-up window is abnormal, the client uploads the pop-up window information to the cloud rule background.

[0081] It is understandable that the client can establish a communication connection with the cloud rule backend in advance, or can establish a communication connection with the cloud rule backend in real time when the preliminary filtering result is a pop-up abnormality. This embodiment does not limit this.

[0082] It should be understood that when the client finds that the pop-up window is abnormal in the initial filtering result, the pop-up window information can be uploaded to the cloud rule backend through the above communication connection.

[0083] Step S30: the cloud rule backend feeds back the cloud rule matching result to the client according to the pop-up window information and the preset cloud rules.

[0084] It should be noted that the preset cloud rules include interception, waiting for user confirmation whether to intercept, and ignoring interception, which is not limited in this embodiment.

[0085] Step S40: the client filters the new pop-up window again according to the cloud rule matching result.

[0086] It is understandable that filtering the new pop-up window again according to the cloud rule matching result may be intercepting the new pop-up window according to the cloud rule matching result and waiting for the user to confirm whether to intercept or ignore it.

[0087] In a first embodiment, a method for filtering advertisement pop-ups is disclosed and applied to a filtering system for advertisement pop-ups. The filtering system for advertisement pop-ups includes: a client and a cloud rule background. When a new pop-up is detected, the client preliminarily filters the new pop-up according to pop-up information. When the preliminary filtering result of the client is that the pop-up is abnormal, the pop-up information is uploaded to the cloud rule background. The cloud rule background feeds back the cloud rule matching result to the client according to the pop-up information and preset cloud rules. The client filters the new pop-up again according to the cloud rule matching result. Since this embodiment performs pop-up filtering by combining local initial screening with cloud matching, it can accurately and timely discover new advertisement pop-ups and formulate reasonable processing rules, thereby improving user experience.

[0088] Reference Figure 2 , Figure 2 This is a flow chart of a second embodiment of the method for filtering advertisement pop-ups of the present invention. Figure 1 The first embodiment shown provides a second embodiment of the method for filtering advertisement pop-up windows of the present invention.

[0089] In the second embodiment, before step S10, the method further includes:

[0090] Step S01: The client enumerates windows and obtains window information.

[0091] It should be understood that in order to accurately detect a new pop-up window, in this embodiment, the new pop-up window is detected by enumerating windows and obtaining window information.

[0092] It can be understood that the enumeration window can be a preset script enumeration window that is called periodically, wherein the preset script can be pre-set.

[0093] Step S02: The client detects a new pop-up window according to the window information.

[0094] It should be understood that detecting a new pop-up window based on window information can be analyzing the window information and detecting the new pop-up window based on the analysis results; it can also be extracting window features from the window information, matching the window features with preset new pop-up window features, and detecting the new pop-up window based on the matching results.

[0095] In the second embodiment, enumerating windows and obtaining window information are disclosed, and new pop-up windows are detected according to the window information. Since enumerating windows is introduced in this embodiment to detect new pop-up windows, the accuracy of detecting new pop-up windows can be improved.

[0096] Furthermore, in order to meet the pop-up window filtering needs of users, the step S02 includes:

[0097] The client obtains the user's marking information for the window;

[0098] The client detects a new pop-up window according to the window information and the mark information.

[0099] It is understandable that in order to meet the pop-up window filtering needs of users, in this embodiment, the user's mark information for the window can also be obtained, and new pop-ups can be detected based on the window information and the mark information. Among them, the mark information can be used to mark whether the window is a new pop-up window.

[0100] In the second embodiment, the step S10 includes:

[0101] Step S101: When the client detects a new pop-up window, it extracts window features from the pop-up window information.

[0102] It should be understood that in order to improve the accuracy of the preliminary filtering of pop-up windows, in this embodiment, window features can be extracted from the pop-up window information, and the new pop-up windows can be preliminarily filtered according to the window features.

[0103] It should be noted that the window characteristics may include window position, window size, window title, window class name, process file signature, application icon and other characteristics, which are not limited in this embodiment.

[0104] Step S102: The client preliminarily filters the new pop-up window according to the window characteristics.

[0105] It is understandable that the preliminary filtering of new pop-up windows according to window features can be to detect whether the new pop-up windows are suspected advertising pop-up windows according to the window features. If so, the preliminary filtering result is that the pop-up windows are abnormal; if not, the preliminary filtering result is that the pop-up windows are normal.

[0106] In the second embodiment, it is disclosed that when a new pop-up window is detected, window features are extracted from the pop-up window information, and the new pop-up window is preliminarily filtered according to the window features; since this embodiment extracts window features from the pop-up window information and preliminarily filters the new pop-up window according to the window features, the accuracy of the preliminary filtering of the pop-up windows can be improved.

[0107] In the second embodiment, the step S40 includes:

[0108] Step S401: The client determines a preset cloud rule that matches successfully according to the cloud rule matching result, and the preset cloud rule includes interception, waiting for user confirmation whether to intercept, and ignoring.

[0109] It should be understood that in order to improve the accuracy of re-filtering of pop-up windows, in this embodiment, the successfully matched preset cloud rules are determined according to the cloud rule matching results, and the new pop-up windows are filtered again according to the successfully matched preset cloud rules.

[0110] Step S402: the client again filters the new pop-up window according to the successfully matched preset cloud rule.

[0111] It is understandable that filtering the new pop-up window again according to the successfully matched preset cloud rule may be to intercept the new pop-up window according to the successfully matched preset cloud rule and wait for the user to confirm whether to intercept or ignore it.

[0112] In a second embodiment, a preset cloud rule that determines a successful match based on the cloud rule matching result is disclosed, the preset cloud rules include interception, waiting for user confirmation whether to intercept, and ignoring, and the new pop-up window is filtered again according to the successfully matched preset cloud rule; since this embodiment determines the successfully matched preset cloud rule based on the cloud rule matching result, and the new pop-up window is filtered again according to the successfully matched preset cloud rule, the accuracy of the pop-up window re-filtering can be improved.

[0113] Furthermore, in order to meet the actual interception requirements of the user, the step S402 includes:

[0114] The client obtains user preference information corresponding to the new pop-up window;

[0115] The client again filters the new pop-up window according to the user preference information and the successfully matched preset cloud rules.

[0116] It should be understood that in order to meet the actual interception needs of users, in this embodiment, the new pop-up window is filtered again based on the user preference information and the successfully matched preset cloud rules.

[0117] It should be noted that the user preference information may be an interception strategy customized by the user according to personal preferences, for example, canceling or adding interception of a certain pop-up window, modifying the interception level, supporting the types of pop-up windows to be intercepted, etc.

[0118] Furthermore, after the client filters the new pop-up window again according to the user preference information and the successfully matched preset cloud rule, it also includes:

[0119] The client receives a filtering strategy fed back by the user according to the new pop-up window;

[0120] The client modifies the user preference information corresponding to the new pop-up window according to the filtering strategy.

[0121] It should be understood that in order to facilitate users to customize user preference information, in this embodiment, it is also possible to receive a filtering strategy fed back by the user based on the new pop-up window, and modify the user preference information corresponding to the new pop-up window based on the filtering strategy.

[0122] Reference Figure 3 , Figure 3 The flowchart of the third embodiment of the method for filtering advertisement pop-ups of the present invention is shown in FIG. Based on the above embodiments, the third embodiment of the method for filtering advertisement pop-ups of the present invention is proposed.

[0123] In the third embodiment, step S30 includes:

[0124] Step S301: the cloud rule backend matches the pop-up window information with a pop-up window sample library, and the pop-up window sample library corresponds to a preset cloud rule.

[0125] Step S302: the cloud rule backend feeds back the cloud rule matching result to the client according to the matching result of the pop-up window information and the pop-up window sample library.

[0126] It should be understood that in order to improve the accuracy of the rule matching results, in this embodiment, the cloud rule background is also used to match the pop-up window information with the pop-up window sample library, and the pop-up window sample library corresponds to the preset cloud rules.

[0127] It should be noted that the pop-up window sample library includes sample features of multiple pop-up window samples.

[0128] It can be understood that matching the pop-up window information with the pop-up window sample library may be matching the pop-up window features with the sample features of the pop-up window samples in the pop-up window sample library.

[0129] Furthermore, the pop-up window samples in the pop-up window sample library are at least one of client report samples, user feedback samples and operator collection samples.

[0130] It is understandable that in order to improve the comprehensiveness of the pop-up window samples, in this embodiment, the pop-up window samples in the pop-up window sample library are at least one of the client reporting samples, user feedback samples and operator collection samples.

[0131] In a third embodiment, the advertisement pop-up filtering system further includes: a sample collection terminal; the method further includes:

[0132] When the cloud rule matching result is a matching failure, the cloud rule backend sends the pop-up window information to the sample collection terminal;

[0133] The sample collection terminal feeds back the storage cloud rules to the cloud rule backend according to the pop-up window information;

[0134] The cloud rule backend adjusts the preset cloud rule according to the incoming cloud rule.

[0135] It should be understood that in order to improve the preset cloud rules, in this embodiment, when the cloud rule matching result is a matching failure, a pop-up message can be sent to the sample collection terminal. The sample collection terminal is used to feedback the cloud rules into the warehouse according to the pop-up message. The cloud rule background is also used to adjust the preset cloud rules according to the cloud rules into the warehouse.

[0136] For ease of understanding, refer to Figure 4 This is for illustration only, but does not limit this solution. Figure 4 This is a device interaction diagram of the filtering system for advertising pop-up windows. In the figure, the client is used to detect and filter suspected advertising pop-up windows, report pop-up window features, and intercept pop-up windows according to cloud rules. The cloud rule backend is used to store cloud rules, match cloud rules according to window features reported by the client, and return them to the client. The sample collection terminal is used to analyze pop-up window samples according to pop-up window information, formulate processing rules, and store them in the database.

[0137] The client periodically calls the preset script to enumerate windows to detect new pop-up windows. After detecting a new window, it obtains the pop-up window features and performs preliminary screening of the new pop-up windows locally based on pop-up window features such as window position and window size. After preliminary screening of suspected advertising pop-up windows, the pop-up window features are uploaded to the cloud rule background, and then the pop-up windows are processed according to the successful matching processing rules returned by the cloud rule background. The pop-up window processing rules are divided into three levels: intercept, wait for the user to decide whether to intercept, and ignore. Users can add or cancel interception according to their preferences. After the user adds interception, it will be automatically intercepted when it pops up again. After the user cancels the interception, it will no longer be intercepted when it pops up again.

[0138] After the cloud rule backend receives the pop-up window features uploaded by the client, it matches the pop-up window features with the pop-up window samples in the pop-up window sample library. If the match is successful, the cloud rules corresponding to the matched pop-up window samples are sent to the client; if the match fails, the pop-up window information is sent to the sample collection terminal.

[0139] After receiving the pop-up information, the sample collection terminal will display the pop-up information to the sample collector, so that the sample collector can analyze the pop-up samples according to the pop-up information, formulate processing rules and store them in the database. In addition to reports from the client, pop-up samples also include user feedback and active collection by operators.

[0140] In addition, refer to Figure 5 , the embodiment of the present invention further proposes a system for filtering advertisement pop-ups, the system for filtering advertisement pop-ups comprising: a client 10 and a cloud rule backend 20;

[0141] The client 10 is used to preliminarily filter a new pop-up window according to pop-up window information when a new pop-up window is detected.

[0142] It should be noted that the client may be pre-installed on the user terminal, wherein the client may be a program corresponding to the cloud rule background and providing local services to the user.

[0143] The cloud rule backend can be a server connected to the Internet for storing and matching cloud rules. In a specific implementation, in order to meet the needs of massive storage and computing, the cloud rule backend is generally a cluster composed of multiple high-performance servers.

[0144] It is understandable that when a new pop-up window is detected, preliminarily filtering the new pop-up window according to the pop-up window information may be to extract window features from the pop-up window information, and preliminarily filtering the new pop-up window according to the window features.

[0145] It should be noted that the window characteristics may include window position, window size, window title, window class name, process file signature, application icon and other characteristics, which are not limited in this embodiment.

[0146] It should be understood that the client can initially filter the new pop-up window according to the window characteristics to detect whether the new pop-up window is a suspected advertising pop-up window. If so, the initial filtering result is that the pop-up window is abnormal; if not, the initial filtering result is that the pop-up window is normal.

[0147] The client 10 is also used to upload the pop-up window information to the cloud rule backend when the preliminary filtering result is that the pop-up window is abnormal.

[0148] It is understandable that the client can establish a communication connection with the cloud rule backend in advance, or can establish a communication connection with the cloud rule backend in real time when the preliminary filtering result is a pop-up abnormality. This embodiment does not limit this.

[0149] It should be understood that when the initial filtering result of the client is that the pop-up window is abnormal, the pop-up window information can be uploaded to the cloud rule backend through the above communication connection.

[0150] The cloud rule backend 20 is used to feed back the cloud rule matching result to the client according to the pop-up window information and the preset cloud rules.

[0151] It should be noted that the preset cloud rules include interception, waiting for user confirmation whether to intercept, and ignoring interception, which is not limited in this embodiment.

[0152] The client 10 is further configured to filter the new pop-up window again according to the cloud rule matching result.

[0153] It is understandable that filtering the new pop-up window again according to the cloud rule matching result may be intercepting the new pop-up window according to the cloud rule matching result and waiting for the user to confirm whether to intercept or ignore it.

[0154] In the present embodiment, a method for filtering advertisement pop-ups is disclosed and applied to a filtering system for advertisement pop-ups. The filtering system for advertisement pop-ups includes: a client and a cloud rule background. When a new pop-up is detected, the client preliminarily filters the new pop-up according to the pop-up information. When the preliminary filtering result of the client is that the pop-up is abnormal, the pop-up information is uploaded to the cloud rule background. The cloud rule background feeds back the cloud rule matching result to the client according to the pop-up information and preset cloud rules. The client filters the new pop-up again according to the cloud rule matching result. Since the present embodiment performs pop-up filtering by combining local initial screening with cloud matching, it can accurately and timely discover new advertisement pop-ups and formulate reasonable processing rules, thereby improving the user experience.

[0155] Based on the above Figure 5 The illustrated embodiment provides a second embodiment of the system for filtering pop-up advertisements of the present invention.

[0156] In the second embodiment, before step S10, the method further includes:

[0157] The client 10 is also used to enumerate windows and obtain window information.

[0158] It should be understood that in order to accurately detect a new pop-up window, in this embodiment, the new pop-up window is detected by enumerating windows and obtaining window information.

[0159] It can be understood that the enumeration window can be a preset script enumeration window that is called periodically, wherein the preset script can be pre-set.

[0160] The client 10 is further configured to detect a new pop-up window according to the window information.

[0161] It should be understood that detecting a new pop-up window based on window information can be analyzing the window information and detecting the new pop-up window based on the analysis results; it can also be extracting window features from the window information, matching the window features with preset new pop-up window features, and detecting the new pop-up window based on the matching results.

[0162] In the second embodiment, enumerating windows and obtaining window information are disclosed, and new pop-up windows are detected according to the window information. Since enumerating windows is introduced in this embodiment to detect new pop-up windows, the accuracy of detecting new pop-up windows can be improved.

[0163] Furthermore, in order to meet the pop-up window filtering needs of the user, the client 10 is also used to obtain the user's marking information for the window;

[0164] The client 10 is further configured to detect a new pop-up window according to the window information and the mark information.

[0165] It is understandable that in order to meet the pop-up window filtering needs of users, in this embodiment, the user's mark information for the window can also be obtained, and new pop-ups can be detected based on the window information and the mark information. Among them, the mark information can be used to mark whether the window is a new pop-up window.

[0166] In the second embodiment, the client 10 is further configured to extract window features from pop-up window information when a new pop-up window is detected.

[0167] It should be understood that in order to improve the accuracy of the preliminary filtering of pop-up windows, in this embodiment, window features can be extracted from the pop-up window information, and the new pop-up windows can be preliminarily filtered according to the window features.

[0168] It should be noted that the window characteristics may include window position, window size, window title, window class name, process file signature, application icon and other characteristics, which are not limited in this embodiment.

[0169] The client 10 is further used to preliminarily filter the new pop-up window according to the window characteristics.

[0170] It is understandable that the preliminary filtering of new pop-up windows according to window features can be to detect whether the new pop-up windows are suspected advertising pop-up windows according to the window features. If so, the preliminary filtering result is that the pop-up windows are abnormal; if not, the preliminary filtering result is that the pop-up windows are normal.

[0171] In the second embodiment, it is disclosed that when a new pop-up window is detected, window features are extracted from the pop-up window information, and the new pop-up window is preliminarily filtered according to the window features; since this embodiment extracts window features from the pop-up window information and preliminarily filters the new pop-up window according to the window features, the accuracy of the preliminary filtering of the pop-up windows can be improved.

[0172] In the second embodiment, the client 10 is further used to determine a preset cloud rule that matches successfully according to the cloud rule matching result, and the preset cloud rule includes interception, waiting for user confirmation whether to intercept, and ignoring.

[0173] It should be understood that in order to improve the accuracy of re-filtering of pop-up windows, in this embodiment, the successfully matched preset cloud rules are determined according to the cloud rule matching results, and the new pop-up windows are filtered again according to the successfully matched preset cloud rules.

[0174] The client 10 is further configured to filter the new pop-up window again according to the successfully matched preset cloud rule.

[0175] It is understandable that filtering the new pop-up window again according to the successfully matched preset cloud rule may be to intercept the new pop-up window according to the successfully matched preset cloud rule and wait for the user to confirm whether to intercept or ignore it.

[0176] In a second embodiment, a preset cloud rule that determines a successful match based on the cloud rule matching result is disclosed, the preset cloud rules include interception, waiting for user confirmation whether to intercept, and ignoring, and the new pop-up window is filtered again according to the successfully matched preset cloud rule; since this embodiment determines the successfully matched preset cloud rule based on the cloud rule matching result, and the new pop-up window is filtered again according to the successfully matched preset cloud rule, the accuracy of the pop-up window re-filtering can be improved.

[0177] Furthermore, in order to meet the actual interception requirements of the user, the client 10 is also used to obtain user preference information corresponding to the new pop-up window;

[0178] The client 10 is further configured to filter the new pop-up window again according to the user preference information and the successfully matched preset cloud rules.

[0179] It should be understood that in order to meet the actual interception needs of users, in this embodiment, the new pop-up window is filtered again based on the user preference information and the successfully matched preset cloud rules.

[0180] It should be noted that the user preference information may be an interception strategy customized by the user according to personal preferences, for example, canceling or adding interception of a certain pop-up window, modifying the interception level, supporting the types of pop-up windows to be intercepted, etc.

[0181] Furthermore, after the client filters the new pop-up window again according to the user preference information and the successfully matched preset cloud rule, it also includes:

[0182] The client 10 is further used to receive a filtering strategy from the user based on the new pop-up window feedback;

[0183] The client 10 is further configured to modify the user preference information corresponding to the new pop-up window according to the filtering strategy.

[0184] It should be understood that in order to facilitate users to customize user preference information, in this embodiment, it is also possible to receive a filtering strategy fed back by the user based on the new pop-up window, and modify the user preference information corresponding to the new pop-up window based on the filtering strategy.

[0185] Reference Figure 6 , Figure 6 The third embodiment of the filtering system for pop-up advertisements of the present invention is a structural block diagram. Based on the above embodiments, the third embodiment of the filtering system for pop-up advertisements of the present invention is proposed.

[0186] In the third embodiment, the cloud rule background 20 is further used to match the pop-up window information with a pop-up window sample library, and the pop-up window sample library corresponds to a preset cloud rule.

[0187] The cloud rule backend 20 is further used to feed back the cloud rule matching result to the client according to the matching result between the pop-up window information and the pop-up window sample library.

[0188] It should be understood that in order to improve the accuracy of the rule matching results, in this embodiment, the cloud rule background is also used to match the pop-up window information with the pop-up window sample library, and the pop-up window sample library corresponds to the preset cloud rules.

[0189] It should be noted that the pop-up window sample library includes sample features of multiple pop-up window samples.

[0190] It can be understood that matching the pop-up window information with the pop-up window sample library may be matching the pop-up window features with the sample features of the pop-up window samples in the pop-up window sample library.

[0191] Furthermore, the pop-up window samples in the pop-up window sample library are at least one of client report samples, user feedback samples and operator collection samples.

[0192] It is understandable that in order to improve the comprehensiveness of the pop-up window samples, in this embodiment, the pop-up window samples in the pop-up window sample library are at least one of the client reporting samples, user feedback samples and operator collection samples.

[0193] In the third embodiment, the advertisement pop-up filtering system further includes: a sample collection terminal 30;

[0194] The cloud rule backend 20 is further configured to send the pop-up window information to the sample collection terminal when the cloud rule matching result is a matching failure;

[0195] The sample collection terminal 30 is used to feed back the storage cloud rules to the cloud rule backend according to the pop-up window information;

[0196] The cloud rule backend 20 is also used to adjust the preset cloud rules according to the incoming cloud rules.

[0197] It should be understood that in order to improve the preset cloud rules, in this embodiment, when the cloud rule matching result is a matching failure, a pop-up message can be sent to the sample collection terminal. The sample collection terminal is used to feedback the cloud rules into the warehouse according to the pop-up message. The cloud rule background is also used to adjust the preset cloud rules according to the cloud rules into the warehouse.

[0198] For ease of understanding, refer to Figure 4 This is for illustration only, but does not limit this solution. Figure 4 This is a device interaction diagram of the filtering system for advertising pop-up windows. In the figure, the client is used to detect and filter suspected advertising pop-up windows, report pop-up window features, and intercept pop-up windows according to cloud rules. The cloud rule backend is used to store cloud rules, match cloud rules according to window features reported by the client, and return them to the client. The sample collection terminal is used to analyze pop-up window samples according to pop-up window information, formulate processing rules, and store them in the database.

[0199] The client periodically calls the preset script to enumerate windows to detect new pop-up windows. After detecting a new window, it obtains the pop-up window features and performs preliminary screening of the new pop-up windows locally based on pop-up window features such as window position and window size. After preliminary screening of suspected advertising pop-up windows, the pop-up window features are uploaded to the cloud rule background, and then the pop-up windows are processed according to the successful matching processing rules returned by the cloud rule background. The pop-up window processing rules are divided into three levels: intercept, wait for the user to decide whether to intercept, and ignore. Users can add or cancel interception according to their preferences. After the user adds interception, it will be automatically intercepted when it pops up again. After the user cancels the interception, it will no longer be intercepted when it pops up again.

[0200] After the cloud rule backend receives the pop-up window features uploaded by the client, it matches the pop-up window features with the pop-up window samples in the pop-up window sample library. If the match is successful, the cloud rules corresponding to the matched pop-up window samples are sent to the client; if the match fails, the pop-up window information is sent to the sample collection terminal.

[0201] After receiving the pop-up information, the sample collection terminal will display the pop-up information to the sample collector, so that the sample collector can analyze the pop-up samples according to the pop-up information, formulate processing rules and store them in the database. In addition to reports from the client, pop-up samples also include user feedback and active collection by operators.

[0202] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0203] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0204] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory image (ROM) / random access memory (RAM), a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0205] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

[0206] The present invention discloses A1, a method for filtering advertisement pop-up windows, the method for filtering advertisement pop-up windows is applied to a filtering system for advertisement pop-up windows, the filtering system for advertisement pop-up windows comprises: a client and a cloud rule background;

[0207] The method for filtering advertisement pop-up windows comprises the following steps:

[0208] When the client detects a new pop-up window, the client preliminarily filters the new pop-up window according to the pop-up window information;

[0209] When the preliminary filtering result is that the pop-up window is abnormal, the client uploads the pop-up window information to the cloud rule backend;

[0210] The cloud rule backend feeds back the cloud rule matching result to the client according to the pop-up window information and the preset cloud rules;

[0211] The client filters the new pop-up window again according to the cloud rule matching result.

[0212] A2. The method for filtering advertisement pop-up windows as described in A1, wherein when the client detects a new pop-up window, the client preliminarily filters the new pop-up window according to the pop-up window information, including:

[0213] When the client detects a new pop-up window, it extracts window features from the pop-up window information;

[0214] The client preliminarily filters the new pop-up window according to the window characteristics.

[0215] A3, as described in A1, the method for filtering advertisement pop-up windows, wherein the client further filters the new pop-up windows according to the cloud rule matching result, comprising:

[0216] The client determines a preset cloud rule that matches successfully according to the cloud rule matching result, wherein the preset cloud rule includes interception, waiting for user confirmation whether to intercept, and ignoring;

[0217] The client again filters the new pop-up window according to the successfully matched preset cloud rule.

[0218] A4, the method for filtering advertisement pop-up windows as described in A3, wherein the client further filters the new pop-up windows according to the successfully matched preset cloud rules, comprising:

[0219] The client obtains user preference information corresponding to the new pop-up window;

[0220] The client again filters the new pop-up window according to the user preference information and the successfully matched preset cloud rules.

[0221] A5. The method for filtering advertisement pop-up windows as described in A4, after the step of the client filtering the new pop-up windows again according to the user preference information and the successfully matched preset cloud rules, further comprises:

[0222] The client receives a filtering strategy fed back by the user according to the new pop-up window;

[0223] The client modifies the user preference information corresponding to the new pop-up window according to the filtering strategy.

[0224] A6. In the method for filtering advertisement pop-ups as described in any one of A1 to A5, the step of the cloud rule backend feeding back a cloud rule matching result to the client according to the pop-up information and preset cloud rules comprises:

[0225] The cloud rule backend matches the pop-up window information with a pop-up window sample library, and the pop-up window sample library corresponds to a preset cloud rule;

[0226] The cloud rule backend feeds back the cloud rule matching result to the client according to the matching result between the pop-up window information and the pop-up window sample library.

[0227] A7. In the method for filtering advertisement pop-up windows as described in A6, the pop-up window samples in the pop-up window sample library are at least one of client-reported samples, user feedback samples, and operator-collected samples.

[0228] A8. The method for filtering pop-up advertisement windows as described in any one of A1 to A5, wherein the system for filtering pop-up advertisement windows further comprises: a sample collection terminal; and the method further comprises:

[0229] When the cloud rule matching result is a matching failure, the cloud rule backend sends the pop-up window information to the sample collection terminal;

[0230] The sample collection terminal feeds back the storage cloud rules to the cloud rule backend according to the pop-up window information;

[0231] The cloud rule backend adjusts the preset cloud rule according to the incoming cloud rule.

[0232] A9. The method for filtering advertisement pop-up windows as described in any one of A1 to A5, wherein before the client detects a new pop-up window, the method further comprises:

[0233] The client enumerates windows and obtains window information;

[0234] The client detects a new pop-up window according to the window information.

[0235] A10. The method for filtering advertisement pop-up windows as described in A9, wherein the step of the client detecting a new pop-up window according to the window information comprises:

[0236] The client obtains the user's marking information for the window;

[0237] The client detects a new pop-up window according to the window information and the mark information.

[0238] The present invention also discloses B11, a filtering system for advertisement pop-up windows, the filtering system for advertisement pop-up windows comprising: a client and a cloud rule background;

[0239] The client is used to preliminarily filter the new pop-up window according to the pop-up window information when a new pop-up window is detected;

[0240] The client is further used to upload the pop-up window information to the cloud rule backend when the preliminary filtering result is that the pop-up window is abnormal;

[0241] The cloud rule backend is used to feed back the cloud rule matching result to the client according to the pop-up information and the preset cloud rules;

[0242] The client is further configured to filter the new pop-up window again according to the cloud rule matching result.

[0243] B12. The advertisement pop-up window filtering system as described in B11, wherein the client is further configured to extract window features from pop-up window information when a new pop-up window is detected;

[0244] The client is also used to preliminarily filter the new pop-up window according to the window characteristics.

[0245] B13, the advertisement pop-up filtering system as described in B11, wherein the client is further used to determine a preset cloud rule that matches successfully according to the cloud rule matching result, wherein the preset cloud rule includes interception, waiting for user confirmation whether to intercept, and ignoring;

[0246] The client is further configured to filter the new pop-up window again according to the successfully matched preset cloud rule.

[0247] B14, the advertising pop-up window filtering system as described in B13, wherein the client is further used to obtain user preference information corresponding to the new pop-up window;

[0248] The client is further configured to filter the new pop-up window again according to the user preference information and the successfully matched preset cloud rules.

[0249] B15, the advertising pop-up window filtering system as described in B14, wherein the client is further used to receive a filtering strategy from the user based on the new pop-up window feedback;

[0250] The client is further used to modify the user preference information corresponding to the new pop-up window according to the filtering strategy.

[0251] B16. The advertisement pop-up filtering system as described in any one of B11 to B15, wherein the cloud rule background is further used to match the pop-up information with a pop-up sample library, and the pop-up sample library corresponds to a preset cloud rule;

[0252] The cloud rule backend is also used to feed back the cloud rule matching result to the client according to the matching result between the pop-up window information and the pop-up window sample library.

[0253] B17. In the advertising pop-up filtering system as described in B16, the pop-up samples in the pop-up sample library are at least one of client-reported samples, user feedback samples, and operator-collected samples.

[0254] B18. The system for filtering pop-up advertisement windows as described in any one of B11 to B15, wherein the system for filtering pop-up advertisement windows further comprises: a sample collection terminal;

[0255] The cloud rule backend is further used to send the pop-up window information to the sample collection terminal when the cloud rule matching result is a matching failure;

[0256] The sample collection terminal is used to feed back the storage cloud rules to the cloud rule backend according to the pop-up window information;

[0257] The cloud rule background is also used to adjust the preset cloud rules according to the incoming cloud rules.

[0258] B19. The system for filtering pop-up advertisements as described in any one of B11 to B15, wherein the client is further used to enumerate windows and obtain window information;

[0259] The client is also used to detect a new pop-up window according to the window information.

[0260] B20, the filtering system for pop-up advertisement windows as described in B19, wherein the client is further used to obtain user marking information for the window;

[0261] The client is further used to detect a new pop-up window according to the window information and the mark information.

Claims

1. A method for filtering advertisement pop-up windows, characterized in that: The method for filtering advertisement pop-up windows is applied to a filtering system for advertisement pop-up windows, and the filtering system for advertisement pop-up windows includes: a client and a cloud rule background; The method for filtering advertisement pop-up windows comprises the following steps: When the client detects a new pop-up window, the client preliminarily filters the new pop-up window according to the pop-up window information; When the preliminary filtering result is that the pop-up window is abnormal, the client uploads the pop-up window information to the cloud rule backend; The cloud rule backend feeds back the cloud rule matching result to the client according to the pop-up window information and the preset cloud rules; The client filters the new pop-up window again according to the cloud rule matching result.

2. The method for filtering advertisement pop-up windows according to claim 1, characterized in that: When the client detects a new pop-up window, the step of preliminarily filtering the new pop-up window according to the pop-up window information includes: When the client detects a new pop-up window, it extracts window features from the pop-up window information; The client preliminarily filters the new pop-up window according to the window characteristics.

3. The method for filtering advertisement pop-up windows according to claim 1, characterized in that: The step of the client filtering the new pop-up window again according to the cloud rule matching result includes: The client determines a preset cloud rule that matches successfully according to the cloud rule matching result, wherein the preset cloud rule includes interception, waiting for user confirmation whether to intercept, and ignoring; The client again filters the new pop-up window according to the successfully matched preset cloud rule.

4. The method for filtering advertisement pop-up windows according to claim 3, characterized in that: The step of the client filtering the new pop-up window again according to the successfully matched preset cloud rule includes: The client obtains user preference information corresponding to the new pop-up window; The client again filters the new pop-up window according to the user preference information and the successfully matched preset cloud rules.

5. The method for filtering advertisement pop-up windows according to claim 4, characterized in that: After the step of filtering the new pop-up window again according to the user preference information and the successfully matched preset cloud rule, the method further includes: The client receives a filtering strategy fed back by the user according to the new pop-up window; The client modifies the user preference information corresponding to the new pop-up window according to the filtering strategy.

6. The method for filtering advertisement pop-up windows according to any one of claims 1 to 5, characterized in that: The step of the cloud rule backend feeding back the cloud rule matching result to the client according to the pop-up window information and the preset cloud rule includes: The cloud rule backend matches the pop-up window information with a pop-up window sample library, and the pop-up window sample library corresponds to a preset cloud rule; The cloud rule backend feeds back the cloud rule matching result to the client according to the matching result between the pop-up window information and the pop-up window sample library.

7. The method for filtering advertisement pop-up windows according to claim 6, characterized in that: The pop-up window samples in the pop-up window sample library are at least one of client report samples, user feedback samples, and operator collection samples.

8. A system for filtering pop-up advertisements, characterized in that: The filtering system for advertisement pop-up windows includes: a client and a cloud rule background; The client is used to preliminarily filter the new pop-up window according to the pop-up window information when a new pop-up window is detected; The client is further used to upload the pop-up window information to the cloud rule backend when the preliminary filtering result is that the pop-up window is abnormal; The cloud rule backend is used to feed back the cloud rule matching result to the client according to the pop-up information and the preset cloud rules; The client is further configured to filter the new pop-up window again according to the cloud rule matching result.

9. The advertisement pop-up filtering system according to claim 8, characterized in that: The client is further used to extract window features from pop-up window information when a new pop-up window is detected; The client is also used to preliminarily filter the new pop-up window according to the window characteristics.

10. The advertisement pop-up filtering system according to claim 8, characterized in that: The client is further used to determine a preset cloud rule that matches successfully according to the cloud rule matching result, wherein the preset cloud rule includes interception, waiting for user confirmation whether to intercept, and ignoring; The client is further configured to filter the new pop-up window again according to the successfully matched preset cloud rule.

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