Method and device for acquiring and pushing advertisement, electronic equipment and readable storage medium

Abstract

The invention relates to an advertisement obtaining and pushing method and device, electronic equipment and a readable storage medium. The advertisement obtaining method comprises the steps that an evaluation result of at least one object category is obtained, and the evaluation result comprises preference information of a user for each object category; generating a target advertisement obtaining request carrying the evaluation result, and sending the target advertisement obtaining request to a server; and obtaining a target advertisement set obtained by screening based on the evaluation result in response to the target advertisement obtaining request by the server. According to the advertisement recommendation method and device, it can be effectively guaranteed that privacy data of the user is not leaked, meanwhile, the advertisement can be accurately pushed to the user based on the target advertisement obtaining request, the advertisement recommendation efficiency is guaranteed, and then the technical problem that in related technologies, advertisement recommendation cannot guarantee user privacy and advertisement recommendation efficiency at the same time can be effectively solved.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technologies, and in particular to a method, device, electronic device, and readable storage medium for acquiring and pushing advertisements. Background Art

[0002] With the increasing international attention to privacy, countries have begun to gradually introduce laws and regulations to restrict access to user behavior information and strictly regulate the use and storage requirements of personal data.

[0003] In related technologies, if the recommendation efficiency of the advertising system needs to be guaranteed, the user's behavior information needs to be obtained, and thus the user's privacy cannot be effectively protected. In other words, related technologies cannot achieve both the recommendation efficiency of the advertising system and the protection of user privacy.

[0004] It can be seen from this that the methods for implementing advertisement recommendation in related technologies have the technical problem of being unable to simultaneously protect user privacy and advertisement recommendation efficiency. Summary of the Invention

[0005] The present disclosure provides a method, device, electronic device, and readable storage medium for acquiring and pushing advertisements to address deficiencies in related technologies.

[0006] According to a first aspect of an embodiment of the present disclosure, a method for obtaining an advertisement is provided, the method comprising:

[0007] Obtaining evaluation results for at least one object category, wherein the evaluation results include user preference information for each object category;

[0008] generating a target advertisement acquisition request carrying the evaluation result, and sending the target advertisement acquisition request to a server;

[0009] A target advertisement set is obtained by the server in response to the target advertisement acquisition request and filtered based on the evaluation result.

[0010] Optionally, the method further includes:

[0011] Acquiring object interaction information of a terminal, wherein the object interaction information includes interaction information between a user and each object on the terminal;

[0012] The evaluation result is determined based on the object interaction information.

[0013] Optionally, determining the evaluation result based on the object interaction information includes:

[0014] Processing the object interaction information according to a preset period to obtain the evaluation result; and / or,

[0015] In a case where the object interaction information indicates that a preset interaction behavior occurs with at least one target object of the terminal, the object interaction information is processed to obtain the evaluation result.

[0016] Optionally, generating a target advertisement acquisition request carrying the evaluation result includes:

[0017] Obtain an original advertisement acquisition request for requesting an advertisement from a server;

[0018] The target advertisement acquisition request is generated according to the original advertisement acquisition request, the processing strategy tag corresponding to the terminal, and the evaluation result, wherein the processing strategy tag is used to indicate whether the server needs to filter and obtain the target advertisement set based on the evaluation result.

[0019] Optionally, the object includes at least one of the following:

[0020] applications, products or services.

[0021] According to a second aspect of an embodiment of the present disclosure, a method for pushing an advertisement is further provided, the method comprising:

[0022] Obtaining a target advertisement acquisition request from a terminal, wherein the target advertisement acquisition request carries an evaluation result, and the evaluation result includes preference information of a user of the terminal for each object category;

[0023] In response to the target advertisement acquisition request, a target advertisement set is obtained by screening based on the evaluation result;

[0024] Pushing the target advertisement set to the terminal.

[0025] Optionally, the filtering and obtaining a target advertisement set based on the evaluation result includes:

[0026] sorting all candidate advertisements according to the evaluation results to obtain sorting results corresponding to all candidate advertisements, wherein the candidate advertisements are advertisements used to promote candidate objects;

[0027] According to the ranking result, a target advertisement is selected from all candidate advertisements;

[0028] The target advertisement set including all the target advertisements is generated.

[0029] Optionally, ranking all candidate advertisements according to the evaluation results to obtain ranking results corresponding to all candidate advertisements includes:

[0030] Determining a terminal score corresponding to each candidate advertisement according to the evaluation result and the object category to which each candidate advertisement belongs;

[0031] Determining an estimated advertising revenue corresponding to each candidate advertisement;

[0032] Determining a final score corresponding to each candidate advertisement based on the terminal score corresponding to each candidate advertisement and the estimated advertising revenue corresponding to each candidate advertisement;

[0033] All the candidate advertisements are sorted according to the final score corresponding to each candidate advertisement to obtain the sorting result.

[0034] Optionally, the method further includes:

[0035] Determining a processing strategy tag in the target advertisement acquisition request;

[0036] If it is determined that the value of the processing strategy flag is the first value, executing a jump operation for jumping to the step of responding to the target advertisement acquisition request and obtaining target advertisement results based on the screening of the evaluation results;

[0037] If it is determined that the value of the processing strategy flag is the second value, subsequent steps are stopped.

[0038] According to a third aspect of an embodiment of the present disclosure, there is further provided an apparatus for obtaining advertisements, including:

[0039] a first acquisition module, configured to acquire evaluation results of at least one object category, wherein the evaluation results include user preference information for each object category;

[0040] A generating module, configured to generate a target advertisement acquisition request carrying the evaluation result, and send the target advertisement acquisition request to a server;

[0041] The second acquisition module is configured to acquire a target advertisement set obtained by the server in response to the target advertisement acquisition request and filtered by the evaluation result.

[0042] Optionally, the device further comprises:

[0043] a third acquisition module, configured to acquire object interaction information of a terminal, wherein the object interaction information includes interaction information between a user and each object on the terminal;

[0044] A result determination module is used to determine the evaluation result based on the object interaction information.

[0045] Optionally, the result determination module is used to:

[0046] Processing the object interaction information according to a preset period to obtain the evaluation result; and / or,

[0047] In a case where the object interaction information indicates that a preset interaction behavior occurs with at least one target object of the terminal, the object interaction information is processed to obtain the evaluation result.

[0048] Optionally, the generating module is used to:

[0049] Obtain an original advertisement acquisition request for requesting an advertisement from a server;

[0050] The target advertisement acquisition request is generated according to the original advertisement acquisition request, the processing strategy tag corresponding to the terminal, and the evaluation result, wherein the processing strategy tag is used to indicate whether the server needs to filter and obtain the target advertisement set based on the evaluation result.

[0051] According to a fourth aspect of an embodiment of the present disclosure, a device for pushing advertisements is further provided, including:

[0052] an acquisition module, configured to acquire a target advertisement acquisition request from a terminal, wherein the target advertisement acquisition request carries an evaluation result, and the evaluation result includes preference information of a user of the terminal for each object category;

[0053] a screening module, configured to respond to the target advertisement acquisition request and screen a target advertisement set based on the evaluation result;

[0054] A push module is used to push the target advertisement set to the terminal.

[0055] Optionally, the screening module includes:

[0056] a ranking unit, configured to rank all candidate advertisements according to the evaluation result, and obtain ranking results corresponding to all candidate advertisements, wherein the candidate advertisements are advertisements for promoting candidate objects;

[0057] a screening unit, configured to screen out a target advertisement from all the candidate advertisements according to the ranking result;

[0058] The generating unit is configured to generate the target advertisement set including all the target advertisements.

[0059] Optionally, the sorting unit is configured to:

[0060] Determining a terminal score corresponding to each candidate advertisement according to the evaluation result and the object category to which each candidate advertisement belongs;

[0061] Determining an estimated advertising revenue corresponding to each candidate advertisement;

[0062] Determining a final score corresponding to each candidate advertisement based on the terminal score corresponding to each candidate advertisement and the estimated advertising revenue corresponding to each candidate advertisement;

[0063] All the candidate advertisements are sorted according to the final score corresponding to each candidate advertisement to obtain the sorting result.

[0064] Optionally, a judgment module is further included, and the judgment module is used to:

[0065] Determining a processing strategy tag in the target advertisement acquisition request;

[0066] If it is determined that the value of the processing strategy flag is the first value, executing a jump operation for jumping to the step of responding to the target advertisement acquisition request and obtaining target advertisement results based on the screening of the evaluation results;

[0067] If it is determined that the value of the processing strategy flag is the second value, subsequent steps are stopped.

[0068] According to a fifth aspect of the embodiments of the present disclosure, there is further provided an electronic device, including a processor;

[0069] a memory for storing processor-executable instructions;

[0070] The processor implements any of the above methods by running the executable instructions.

[0071] According to a sixth aspect of an embodiment of the present disclosure, a computer-readable storage medium is further provided, on which a computer program is stored. When the program is executed by a processor, the steps in the method described in any of the above embodiments are implemented.

[0072] The technical solutions provided by the embodiments of the present disclosure may have the following beneficial effects:

[0073] It can be seen from the above embodiments that the present disclosure provides a method for obtaining advertisements, which obtains evaluation results of at least one object category, wherein the evaluation results include the user's preference information for each object category; generates a target advertisement acquisition request carrying the evaluation results, and sends the target advertisement acquisition request to the server; obtains a target advertisement set obtained by the server based on the evaluation results screening; the present disclosure can directly generate evaluation results on the user side, and generate a target advertisement acquisition request carrying the evaluation results, so the server does not need to collect the user's privacy data to determine the preference information to determine the target advertisement acquisition request, which can effectively protect the user's privacy data from being leaked. At the same time, it can also accurately push advertisements to users based on the target advertisement acquisition request, thereby ensuring the efficiency of advertisement recommendation, and thus effectively solving the technical problem in related technologies that advertisement recommendation cannot simultaneously protect user privacy and advertisement recommendation efficiency.

[0074] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0076] Figure 1 It is a schematic flow chart of a method for obtaining advertisements according to an embodiment of the present disclosure.

[0077] Figure 2 It is a schematic flow chart of another method for obtaining advertisements according to an embodiment of the present disclosure.

[0078] Figure 3 It is a schematic flow chart of another method for obtaining advertisements according to an embodiment of the present disclosure.

[0079] Figure 4 This is a schematic flowchart of a method for pushing advertisements according to an embodiment of the present disclosure.

[0080] Figure 5 It is a schematic flow chart of another method for pushing advertisements according to an embodiment of the present disclosure.

[0081] Figure 6 It is a schematic flow chart of another method for pushing advertisements according to an embodiment of the present disclosure.

[0082] Figure 7This is a schematic flow chart showing an embodiment of obtaining and pushing advertisements according to an embodiment of the present disclosure.

[0083] Figure 8 This is a schematic block diagram of a device for acquiring advertisements according to an embodiment of the present disclosure.

[0084] Figure 9 This is a schematic block diagram of a device for pushing advertisements according to an embodiment of the present disclosure.

[0085] Figure 10 It is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.

[0086] Figure 11 It is a schematic block diagram of a device for obtaining advertisements according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0087] The following will be combined with the accompanying drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the embodiments described are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present disclosure.

[0088] The terms used in the embodiments of the present disclosure are for the purpose of describing specific embodiments only and are not intended to limit the embodiments of the present disclosure. The singular forms "a," "an," and "the" used in the embodiments of the present disclosure and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0089] It should be understood that although the terms first, second, third, etc. may be used to describe various information in the embodiments of the present disclosure, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of the embodiments of the present disclosure, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0090] For the purpose of brevity and ease of understanding, the terms "greater than," "less than," "higher than," and "lower than" are used herein to describe size relationships. However, those skilled in the art will understand that the term "greater than" also encompasses the meaning of "greater than or equal to," and "less than" also encompasses the meaning of "less than or equal to," and the term "higher than" also encompasses the meaning of "higher than or equal to," and "lower than" also encompasses the meaning of "lower than or equal to."

[0091] Figure 1 The following is a schematic flow chart of a method for obtaining advertisements according to an embodiment of the present disclosure. The method for obtaining advertisements shown in this embodiment can be executed by a terminal, including but not limited to a mobile phone, tablet computer, wearable device, sensor, IoT device, or other communication device.

[0092] like Figure 1 As shown, the method for obtaining advertisements may include the following steps:

[0093] Step S101: obtaining evaluation results of at least one object category, wherein the evaluation results include user preference information for each object category.

[0094] Specifically, the evaluation results for at least one object category can be determined based on the object interaction information recorded when the user uses the terminal. The object category can be the category corresponding to each object, and the object may include, but is not limited to, applications, goods, or services. When the object is an application, the object category may include, but is not limited to, gaming applications, educational applications, social applications, shopping applications, and entertainment applications. When the object is a good, the object category may include, but is not limited to, daily necessities, food, digital appliances, household items, etc. When the object is a service, the object category may include, but is not limited to, cloud computing services, cloud storage services, online promotion services, online live streaming services, etc.

[0095] The evaluation result of at least one object category may be preference information indicating a preference for each object category in the at least one object category, and the preference information corresponding to each object category may be used to indicate the user's interest level in the preference information.

[0096] like Figure 2 As shown, as an optional embodiment, the evaluation result in step S101 can be determined through the following steps S201 and S202, including:

[0097] Step S201: Acquire object interaction information of a terminal, wherein the object interaction information includes interaction information between a user and each object on the terminal.

[0098] Specifically, the terminal in this embodiment can be a terminal device, or all terminal devices associated with an account, or terminal devices in the same network environment, etc. The devices included in the terminal can be limited according to the usage scenario.

[0099] The terminal's object interaction information can be stored as encrypted data in the terminal's encrypted database. The encrypted database is a database that requires certain permissions to access. Furthermore, the encrypted database can also be a database that cannot be accessed by a remote server, so as to further improve the security of user privacy data.

[0100] In Example 1, the following method can be used to illustrate how to obtain the interaction information of an object, taking the object as an application (ie, app) as an example:

[0101] In this example, the above-mentioned object interaction information can be collected by the terminal intelligent program on the terminal. The terminal intelligent program refers to a software program with certain intelligent capabilities running on the terminal. Compared with the cloud intelligent program, the terminal intelligent program does not need to rely on the Internet connection and can perform data processing and decision-making locally. This enables smart devices to make intelligent decisions and interactions more independently, providing users with a better user experience.

[0102] The terminal intelligent program does not collect advertising IDs (a unique ID provided by Google Play services for advertising services that can be reset by the user). It only collects real-time record data such as the terminal user's app installation sequence, user app uninstallation sequence, user app opening sequence, and user installed app list, and stores the above record data in the terminal in an encrypted database format. Furthermore, in order to avoid changes in user preferences or record data occupying too much memory space, the record data in the encrypted database can be set to be stored for no more than 30 days. In addition, due to the same memory usage issue, unnecessary raw data can be dynamically cleared (for example, data that cannot represent user preferences, erroneous data, duplicate data, etc.).

[0103] Optionally, the list of object interaction item parameters (included in the object interaction information) that need to be collected may include but is not limited to the following categories:

[0104] 1. The user's app usage behavior sequence, for example, which types of apps are used in different time intervals. Furthermore, the apps used in each time interval can be determined by obtaining the opening and closing behaviors of each app. In addition, this behavior sequence can be updated in real time.

[0105] 2. The number of times and duration of user use of the app. For any app, the number of times can be determined through all the time intervals corresponding to the user's use of the app (the number of times is the number of time intervals in which the app has been used, which can effectively avoid the situation where the user's brief exit and re-entry is regarded as a new use of the app). For example, when each natural hour is regarded as a time interval (for example, 10:00:00 to 10:59:59, 11:00:00 to 11:59:59, 12:00:00 to 12:59:59, etc.), and the time intervals corresponding to the app include 9:00:00 to 9:59:59 and 18:00:00 to 18:59:59, then it can be determined that the app corresponds to two time intervals, and the duration of the app can be accumulated based on the single duration of each use of the app.

[0106] 3. The user's behavior sequence for installing apps, that is, determining the time interval corresponding to the installation moment of each app.

[0107] 4. The user's first app launch behavior sequence, that is, determining the time interval corresponding to the first launch of each app.

[0108] 5. The user's behavior sequence for uninstalling apps, that is, determining the time interval corresponding to the uninstallation moment of each app.

[0109] 6. List of apps installed on the user’s phone.

[0110] 7. User’s mobile phone model, region, language, time, network, etc.

[0111] The following advantages are achieved by using intelligent programs on the terminal to collect data: first, user data will not be sent to the server, avoiding the risk of user privacy data being leaked during transmission; second, feature data collection, model inference, and business logic are all completed on the terminal side, without the need for network interaction, and can perceive user status in more real time.

[0112] In Example 2, the following method can be used to obtain interaction information about a product: The following information can be stored in an encrypted database: 1. The time at which the user clicked on the purchase link or advertisement corresponding to each product; 2. The duration for which the user browsed the purchase information or advertisement corresponding to each product. The click time and browsing duration are then determined as interaction information.

[0113] Step S202: determining an evaluation result based on the object interaction information.

[0114] Specifically, after the object interaction information is determined, the evaluation result may be determined using the following method: 1. Target object interaction item parameters used to determine the evaluation result may be determined from among all object interaction item parameters;

[0115] 2. Then determine the scoring information corresponding to the interaction item parameters of each target object.

[0116] 3. Integrate and process the rating information (for example, directly package, weight, etc.) to obtain the evaluation result.

[0117] For example, the evaluation results include the object category number that the user is interested in (i.e., the number that corresponds one-to-one to the object category) and the weight corresponding to the object category. For example, when the object category is an educational application and the corresponding weight is 0.2, the rating information corresponding to the educational application can be (educational application, 0.2). Furthermore, the sum of the weights corresponding to all object categories is 1.

[0118] Step S102: Generate a target advertisement acquisition request carrying the evaluation result, and send the target advertisement acquisition request to the server.

[0119] Specifically, after obtaining the evaluation result, the evaluation result can be packaged together with an advertising request (used to request an advertisement from the server) to obtain a target advertising acquisition request carrying the evaluation result; in addition, the evaluation result can be used as the value of one or more fields in the target advertising acquisition request to obtain a target advertising acquisition request carrying the evaluation result.

[0120] After the target advertisement acquisition request is generated, the target advertisement acquisition request may be sent to the server via remote communication with the server.

[0121] Step S103: obtaining a target advertisement set obtained by the server in response to the target advertisement acquisition request and screening based on the evaluation result.

[0122] Specifically, after receiving the target advertisement acquisition request from the terminal, the server determines that the advertisement required by the terminal needs to be recalled. Therefore, the target advertisement acquisition request can be parsed according to the parsing method corresponding to the generation method of the target advertisement acquisition request, so as to obtain the evaluation results carried therein.

[0123] After obtaining the evaluation results, the server can recall advertisements according to the user's preference information for each object category in the evaluation results, obtain target advertisements for the object categories that the user is interested in, and then obtain a target advertisement set including all target advertisements, and finally send the target advertisement set to the terminal; at this point, the terminal can obtain the target advertisement set from the server.

[0124] This embodiment obtains evaluation results of at least one object category on the user side, wherein the evaluation results include the user's preference information for each object category; generates a target advertisement acquisition request carrying the evaluation results, and sends the target advertisement acquisition request to the server; obtains a target advertisement set obtained by the server based on the evaluation results; thereby directly generating the evaluation results on the user side and generating the target advertisement acquisition request carrying the evaluation results. Therefore, the server does not need to collect the user's privacy data to determine the preference information to determine the target advertisement acquisition request, which can effectively protect the user's privacy data from being leaked. At the same time, it can also accurately push advertisements to the user based on the target advertisement acquisition request, thereby ensuring the efficiency of advertisement recommendation, and thus effectively solving the technical problem in related technologies that advertisement recommendation cannot simultaneously protect user privacy and advertisement recommendation efficiency.

[0125] As an optional embodiment, step S202 in the aforementioned embodiment is implemented to determine the evaluation result based on the object interaction information in the following manner: feature calculation is performed on the object interaction information to obtain feature data; the feature data is passed into the interest evaluation model to obtain preference information corresponding to each object category output by the interest evaluation model.

[0126] Specifically, after determining the object interaction information, feature calculation can be performed on the object interaction information to obtain feature data for attributes related to user preferences, and then the feature data can be passed to the terminal's preset interest evaluation model (for example, tensorflow lite, an open source deep learning framework that runs tensorflow models on the device side) for calculation to obtain the output of the interest evaluation model to characterize the user's preference information for each object category (for example, the score corresponding to each object category). After obtaining the preference information, all the preference information can be integrated to obtain the evaluation result.

[0127] Furthermore, after obtaining the evaluation information, the evaluation information may be encrypted to obtain an encrypted data file, and then stored.

[0128] Since users can start, exit, and update apps on their terminals at any time, object interaction information may change at any time, and the frequency of changes is very high. If the corresponding evaluation results must be obtained every time the object interaction information changes, the processing volume will be very high. In addition, since the computing resources of the terminal are limited, if the computing resources of the terminal are occupied for a long time in order to make advertising requests, the computing resources available for allocation to other applications or programs will inevitably be reduced. In addition, not every user's operation will have a significant impact on the object interaction information, and thus will not have a significant impact on the final advertising request. In order to overcome the above technical problems, such as Figure 3 As shown, as an optional embodiment, the step S202 of the aforementioned embodiment of determining the evaluation result based on the object interaction information can be implemented by the following related methods of step S301 and / or S302:

[0129] Step S301: Process the object interaction information according to a preset period to obtain an evaluation result.

[0130] That is, the latest object interaction information can be processed according to a preset period and the latest evaluation result can be obtained.

[0131] Optionally, the preset period may be a pre-set period for obtaining evaluation results based on object interaction information processing, for example, 1 hour, 6 hours, 24 hours, etc. The specific length of the preset period may be selected according to the actual application scenario.

[0132] Furthermore, when processing the object interaction information according to a preset period, it is also possible to determine whether the object interaction information has changed relative to the previous object interaction information. The previous object interaction information is the object interaction information that is a preset period away from the current object interaction information. That is to say, it is possible to determine whether the latest object interaction information has changed relative to the previous object interaction information according to the preset period. When the latest object interaction information has changed relative to the previous object interaction information, a corresponding evaluation result is generated based on the latest object interaction information. When the latest object interaction information has not changed relative to the previous object interaction information, the latest high-interaction information is not processed, and there is no need to generate an evaluation result.

[0133] Step S302: When the object interaction information indicates that at least one target object of the terminal has a preset interaction behavior, the object interaction information is processed to obtain an evaluation result.

[0134] Specifically, the object interaction information may include the interaction behavior of each object on the terminal, and objects that experience preset interaction behaviors are recorded as target objects. Preset interaction behaviors can be preset and require special attention, and may include but are not limited to: user installation of an application, user uninstallation of an application, and user first login to an application. When it is determined that the object interaction information indicates that at least one target object of the terminal has experienced any of all preset interaction behaviors, the object interaction information is processed to obtain an evaluation result.

[0135] With the method of this embodiment, it is unnecessary to frequently process object interaction information to obtain evaluation results, which can effectively save computing resources of the terminal.

[0136] As an optional embodiment, step S102 in the aforementioned embodiment to generate a target advertisement acquisition request carrying the evaluation result can be implemented in the following related manner: obtaining the original advertisement acquisition request for requesting the server to obtain advertisements; generating a target advertisement acquisition request based on the original advertisement acquisition request, the processing strategy tag corresponding to the terminal, and the evaluation result, wherein the processing strategy tag is used to indicate whether the server needs to filter and obtain the target advertisement set based on the evaluation result.

[0137] Specifically, in order to request an advertisement from the server, an original advertisement acquisition request capable of acquiring advertisements is required. The server recalls advertisements in response to the original advertisement acquisition request and returns one or more of the recalled advertisements to the terminal. In this embodiment, since the evaluation results also need to be sent to the server and the server needs to screen advertisements according to the evaluation results, when generating the target advertisement acquisition request, in addition to the above-mentioned original advertisement acquisition request, the original advertisement acquisition request and a processing strategy tag for indicating whether the server needs to screen advertisements based on the evaluation results are also required; the processing strategy tag can be an identification information and is agreed upon in advance with the server. When the processing strategy tag is included, the server needs to filter the target advertisement set based on the evaluation results.

[0138] like Figure 4 According to another aspect of the present disclosure, a method for pushing advertisements is provided, the method comprising the following steps:

[0139] Step S401: Obtain a target advertisement acquisition request from a terminal, wherein the target advertisement acquisition request carries an evaluation result, and the evaluation result includes preference information of the terminal user for each object category.

[0140] Step S402: Filter and obtain a target advertisement set based on the evaluation results.

[0141] Step S403: Push the target advertisement set to the terminal.

[0142] Specifically, the method for pushing advertisements in this embodiment can be applied to a server. The terminal can determine the evaluation result of at least one object category through the object interaction information recorded when the user uses the terminal. The object category can be a category corresponding to each object. After obtaining the evaluation result, the terminal can package the evaluation result together with the advertisement request (used to request advertisements from the server) to obtain a target advertisement acquisition request carrying the evaluation result; in addition, the evaluation result can be used as the value of one or more fields in the target advertisement acquisition request to obtain a target advertisement acquisition request carrying the evaluation result. After generating the target advertisement acquisition request, the terminal can send the target advertisement acquisition request to the server through remote communication with the server.

[0143] After receiving the target advertisement acquisition request from the terminal, the server may parse the target advertisement acquisition request according to a parsing method corresponding to the generation method of the target advertisement acquisition request, thereby obtaining the evaluation result carried therein.

[0144] After obtaining the evaluation results, the server can recall advertisements according to the user's preference information for each object category in the evaluation results, obtain target advertisements for the object categories that the user is interested in, and then obtain a target advertisement set including all target advertisements, and finally send the target advertisement set to the terminal.

[0145] In this embodiment, the server only obtains the target advertisement acquisition request from the terminal, and the generation of the target advertisement acquisition request is implemented on the terminal; therefore, the server does not need to collect the privacy data of the terminal to determine the preference information to determine the target advertisement acquisition request, which can effectively protect the user's privacy data from being leaked. At the same time, it can also accurately push advertisements to users based on the target advertisement acquisition request, thereby ensuring the efficiency of advertisement recommendation, and thus effectively solving the technical problem that the method for implementing advertisement recommendation in the related art cannot ensure both user privacy and advertisement recommendation efficiency.

[0146] like Figure 5 As shown, as an optional embodiment, the step S402 of the aforementioned embodiment of filtering and obtaining the target advertisement set based on the evaluation results can be implemented by the following related methods of steps S501 to S503:

[0147] Step S501 : sorting all candidate advertisements according to the evaluation results to obtain sorting results corresponding to all candidate advertisements, wherein the candidate advertisements are advertisements used to promote candidate objects.

[0148] Specifically, since the evaluation result includes the preference information of the terminal user for each object category, all candidate advertisements can be sorted according to the preference information to obtain a sorting result.

[0149] The candidate advertisements may be advertisements requested by advertisers for exposure, and each candidate advertisement may be sorted according to the degree of preference indicated by the preference information. Optionally, the sorting result may be the result obtained by sorting all candidate advertisements in descending order according to the preference program, or the result obtained by sorting all candidate advertisements in descending order according to the preference program.

[0150] Step S502: Filter out the target advertisement from all candidate advertisements according to the ranking result.

[0151] Specifically, after the ranking result is determined, the target number of advertisements to be pushed to the user may be determined, and target advertisements with a high target number of preferences may be screened out from all candidate advertisements.

[0152] Step S503: Generate a target advertisement set including all target advertisements.

[0153] Specifically, after all target advertisements are screened and obtained, all target advertisements may be packaged to obtain a target advertisement set.

[0154] The method of this embodiment provides a method for quickly screening advertisements and selecting advertisements that meet the evaluation results, so that the target advertisement set finally generated can effectively meet the user's preferences.

[0155] like Figure 6 As shown, as an optional embodiment, the following steps S601 to S604 can be used to implement the aforementioned step S501 of the embodiment, in which all candidate advertisements are sorted according to the evaluation results, to obtain a sorting result corresponding to all candidate advertisements, including:

[0156] Step S601 : Determine a terminal score corresponding to each candidate advertisement according to the evaluation result and the object category to which each candidate advertisement belongs.

[0157] Specifically, the evaluation results include the terminal user's preference information for each object category. Each preference information may have a corresponding terminal score, and therefore, each object category may have a corresponding terminal score. Optionally, the terminal score may be a score representing the degree of preference indicated by the preference information. Furthermore, the higher the terminal score, the higher the degree of preference indicated by the preference information.

[0158] Based on this, the terminal score corresponding to each object category can be determined as the terminal score of each candidate advertisement according to the object category described by each candidate advertisement.

[0159] Step S602: Determine the estimated advertising revenue corresponding to each candidate advertisement.

[0160] Specifically, the estimated advertising revenue of each candidate advertisement can be determined by obtaining the corresponding quotation of each candidate advertisement on the advertising bidding platform.

[0161] Step S603 : determining a final score corresponding to each candidate advertisement based on the terminal score corresponding to each candidate advertisement and the estimated advertisement revenue corresponding to each candidate advertisement.

[0162] Specifically, when pushing advertisements, it is necessary to consider not only user preferences but also advertisement revenue. Therefore, when determining the terminal score corresponding to each candidate advertisement, it is necessary to combine the terminal score and the estimated advertisement revenue. Optionally, the following two formulas can be used to determine the final score (rankscore):

[0163] Formula 1: rankscore=peCPM+K*sortweight;

[0164] Formula 2: rankscore=peCPM*sortweight*K;

[0165] Among them, peCPM is the estimated advertising revenue, sortweight is the terminal score, and K is an adjustable weighting factor, which can be used to adjust the weight of the terminal score and terminal intelligent interest.

[0166] Optionally, any one of the above formulas may be used to determine the final score, or the results determined by the above formulas 1 and 2 may be weighted to obtain the final score.

[0167] Step S604: sort all candidate advertisements according to the final score corresponding to each candidate advertisement to obtain a sorting result.

[0168] Specifically, after determining the final score corresponding to each candidate advertisement, all candidate advertisements may be sorted in order of score to obtain a sorting result. For example, the final scores may be sorted from high to low to obtain a sorting result.

[0169] After obtaining the target advertisement acquisition request from the terminal in step S401, since the target advertisement acquisition request does not necessarily indicate the need for advertisement screening, the specific steps to be performed subsequently need to be determined based on the processing strategy tag. Therefore, as an optional embodiment, between obtaining the target advertisement acquisition request from the terminal in step S401 and obtaining the target advertisement set based on the screening of the evaluation results in step S402, the method further includes the following steps: determining the processing strategy tag in the target advertisement acquisition request; when it is determined that the value of the processing strategy tag is the first value, executing a jump operation for jumping to the step of responding to the target advertisement acquisition request and obtaining the target advertisement result based on the screening of the evaluation results; when it is determined that the value of the processing strategy tag is the second value, stopping execution of subsequent steps.

[0170] That is, after obtaining the target advertisement acquisition request, the processing strategy tag can be determined therefrom, and the value of the processing strategy tag can be read to determine whether the value is the first value or the second value.

[0171] The first value may be a value indicating that advertisement screening needs to be performed according to the evaluation results, and the second value may be a value indicating that advertisement screening does not need to be performed according to the evaluation results. For example, the first value may be 1 and the second value may be 0. In addition, the first value and the second value may also adopt other value-taking methods, which are not limited here.

[0172] When it is determined that the value of the processing strategy tag is the first value, that is, it is necessary to screen advertisements according to the evaluation results, and then a jump operation for jumping to step S402 can be executed; when it is determined that the value of the processing strategy tag is the second value, subsequent steps S402 and S403 are stopped, and the traditional method of obtaining privacy data from the terminal to screen advertisements can be adopted, and the screened advertisements can be pushed to the terminal.

[0173] like Figure 7 As shown, taking a mobile phone as a terminal and an app as an object as an example, an embodiment of obtaining and pushing advertisements by applying the method described in any of the above embodiments is provided:

[0174] 1. Smart data processing strategy for mobile phone clients

[0175] 1.1 Data collection phase:

[0176] Collection of end-user privacy data (i.e., object interaction information): When a user interacts with an app on their phone, the object interaction information is updated. In this solution, the phone can collect privacy data through the end-user smart program, and the end-user smart program does not collect the advertising ID (a unique ID that can be reset by the user and provided by Google Play Services for advertising services). It only collects various object interaction project parameters in real time, such as the list of apps installed on the phone, the user's behavior sequence for uninstalling apps, the user's behavior sequence for launching apps for the first time, and the user's behavior sequence for installing apps. The object interaction information obtained is stored in the user's device in an encrypted database format, and the object interaction information is stored for no more than 30 days. In addition, considering memory issues, the client will dynamically clear unnecessary raw data.

[0177] The list of object interaction item parameters (included in the object interaction information) that need to be collected may include but is not limited to the following categories:

[0178] (1) The user's behavior sequence in using apps, for example, what type of apps are used in different time intervals. The apps used in each time interval can be further determined by obtaining the opening and closing behaviors of each app. In addition, the behavior sequence can be updated in real time.

[0179] (2) The number of times and duration of a user's use of an app. For any app, the number of times can be determined through all the time intervals corresponding to the user's use of the app (the number of times is the number of time intervals in which the app has been used, which can effectively avoid the situation where a user's brief exit and re-entry is regarded as a new use of the app). For example, when each natural hour is regarded as a time interval (for example, 10:00:00 to 10:59:59, 11:00:00 to 11:59:59, 12:00:00 to 12:59:59, etc.), and the time intervals corresponding to the app include 9:00:00 to 9:59:59 and 18:00:00 to 18:59:59, then it can be determined that the app corresponds to two time intervals, and the duration of the app can be accumulated based on the single duration of each use of the app.

[0180] (3) The user’s behavior sequence for installing apps, i.e., determining the time interval corresponding to the installation moment of each app.

[0181] (4) The behavior sequence of the user’s first launch app, that is, determining the time interval corresponding to the first launch of each app.

[0182] (5) The behavior sequence of users uninstalling apps, that is, determining the time interval corresponding to the uninstallation moment of each app.

[0183] (6) List of apps installed on the user’s phone.

[0184] (7) User’s mobile phone model, region, language, time, network, etc.

[0185] Collecting data through terminals has the following advantages: First, user data will not be sent to the server, avoiding the risk of user privacy data being leaked during transmission; second, feature data collection, model inference, and business logic are all completed on the terminal side, without the need for network interaction, and can perceive user status in more real time.

[0186] 1.2. Object interaction information processing and model calculation stage:

[0187] After collecting the object interaction information, the object interaction information is subjected to feature calculation to obtain feature data, which can be stored. The feature data is then passed to tensorflow lite (i.e., an intent understanding engine, i.e., the interest evaluation model described in the aforementioned embodiment) for calculation to obtain the user's interest scores for various apps (i.e., preference information) and store the above interest scores in encrypted data files. When the user behavior changes (i.e., when the object interaction information changes), the interest scores are updated in real time. Model calculation adopts two modes: timed calculation and instant calculation. Timed calculation refers to the regular (i.e., preset period) detection of whether the feature data is updated compared to the data used for the last calculation. If updated, the model is triggered for calculation; instant calculation triggers the above tensorflow lite calculation when a preset interaction behavior occurs (such as: user installs the application, user uninstalls the application, user logs in to the application for the first time, etc.).

[0188] 1.3 Data transmission stage:

[0189] When a mobile phone needs to make an advertisement request, the mobile phone can assemble the advertisement request according to the evaluation result, obtain the target advertisement acquisition request, and then send the target advertisement acquisition request to the advertisement bidding platform of the server, thereby sending the real-time evaluation result to the server. The detailed format of each preference information in the evaluation result can be: the app number that the user is interested in + the weight corresponding to the app.

[0190] 2. The server executes the ad reordering strategy:

[0191] 2.1. After the server recalls the advertisement, it will re-arrange the advertisement:

[0192] When the advertising request contains a processing strategy tag, the advertising engine in the advertising system adds an end-to-end intelligent reordering link. The end-to-end intelligent reordering uses the evaluation results uploaded by the mobile phone to increase the advertising weight of advertisements that the user is interested in. After the reordering, the sorted advertising list needs to be filtered (that is, deleting advertisements that do not meet the requirements) and truncated (that is, selecting the required number of advertisements), so as to finally filter out the target advertising set that the user is interested in.

[0193] Compared with traditional advertising systems, an end-to-end intelligent re-ranking link has been added, which directly intervenes in the final sorting of advertisements based on the interest classification of real-time requests. The advantage is that it can use the real-time evaluation results of users. Compared with the traditional T+1 (T is the current moment, T+1 is the next moment) advertising system, real-time re-ranking will have higher recommendation accuracy for users and will also improve the distribution efficiency of the entire advertising system.

[0194] 2.2. Rearrange the formula:

[0195] The following two formulas are introduced for the re-ranking phase to determine the final score (rankscore):

[0196] Formula 1: rankscore=peCPM+K*sortweight;

[0197] Formula 2: rankscore=peCPM*sortweight*K;

[0198] Among them, peCPM is the estimated advertising revenue, sortweight is the terminal score, and K is an adjustable weighting factor, which can be used to adjust the weight of the terminal score and terminal intelligent interest.

[0199] 3. Advertisement return

[0200] The target ad set is packaged on the ad bidding platform to obtain a packaged result (including the target ad set) that meets the requirements of the mobile terminal, and the packaged result is sent to the terminal for display and embedding.

[0201] Optionally, any one of the above formulas may be used to determine the final score, or the results determined by the above formulas 1 and 2 may be weighted to obtain the final score.

[0202] like Figure 8 As shown, corresponding to the embodiment of the method for obtaining advertisements applied to a terminal, the present disclosure further provides an embodiment of an apparatus for obtaining advertisements applied to a terminal, including:

[0203] A first acquisition module 81 is configured to acquire evaluation results of at least one object category, wherein the evaluation results include user preference information for each object category;

[0204] A generating module 82 is configured to generate a target advertisement acquisition request carrying the evaluation result, and send the target advertisement acquisition request to the server;

[0205] The second acquisition module 83 is configured to acquire a target advertisement set obtained by the server in response to the target advertisement acquisition request and filtered based on the evaluation result.

[0206] As an optional embodiment, the apparatus for obtaining advertisements applied to a terminal further includes:

[0207] a third acquisition module, configured to acquire object interaction information of the terminal, wherein the object interaction information includes interaction information between the user and each object on the terminal;

[0208] The result determination module is used to determine the evaluation result based on the object interaction information.

[0209] As an optional embodiment, the third acquisition module is configured to:

[0210] Perform feature calculation on object interaction information to obtain feature data;

[0211] The feature data is input into the interestingness evaluation model to obtain the preference information corresponding to each object category output by the interestingness evaluation model.

[0212] As an optional embodiment, the result determination module is configured to:

[0213] Processing the object interaction information according to a preset period to obtain an evaluation result; and / or,

[0214] In a case where the object interaction information indicates that at least one target object of the terminal has a preset interaction behavior, the object interaction information is processed to obtain an evaluation result.

[0215] As an optional embodiment, the generating module 82 is configured to:

[0216] Obtain an original advertisement acquisition request for requesting an advertisement from a server;

[0217] A target advertisement acquisition request is generated according to the original advertisement acquisition request, the processing strategy tag corresponding to the terminal, and the evaluation result, wherein the processing strategy tag is used to indicate whether the server needs to filter and obtain the target advertisement set based on the evaluation result.

[0218] As an optional embodiment, the object includes at least one of the following:

[0219] applications, products or services.

[0220] like Figure 9 As shown, corresponding to the embodiment of the method for pushing advertisements applied to the server, the present disclosure further provides an embodiment of an apparatus for pushing advertisements, including:

[0221] An acquisition module 91 is configured to acquire a target advertisement acquisition request from a terminal, wherein the target advertisement acquisition request carries an evaluation result, and the evaluation result includes preference information of the terminal user for each object category;

[0222] A screening module 92 is configured to respond to a target advertisement acquisition request and screen a target advertisement set based on the evaluation result;

[0223] The push module 93 is used to push the target advertisement set to the terminal.

[0224] As an optional embodiment, the screening module 92 includes:

[0225] a ranking unit, configured to rank all candidate advertisements according to the evaluation results, and obtain ranking results corresponding to all candidate advertisements, wherein the candidate advertisements are advertisements used to promote the candidate objects;

[0226] A screening unit, configured to screen out a target advertisement from all candidate advertisements according to the ranking result;

[0227] The generating unit is configured to generate a target advertisement set including all target advertisements.

[0228] As an optional embodiment, the sorting unit is configured to:

[0229] Determine a terminal score corresponding to each candidate advertisement according to the evaluation results and the object category to which each candidate advertisement belongs;

[0230] Determining an estimated advertising revenue corresponding to each candidate advertisement;

[0231] Determining a final score corresponding to each candidate advertisement based on the terminal score corresponding to each candidate advertisement and the estimated advertising revenue corresponding to each candidate advertisement;

[0232] All candidate advertisements are sorted according to the final score corresponding to each candidate advertisement to obtain a sorting result.

[0233] As an optional embodiment, the system further includes a judgment module, which is configured to:

[0234] Determining a processing strategy tag in a target advertisement acquisition request;

[0235] If it is determined that the value of the processing strategy flag is the first value, executing a jump operation for jumping to the screening module 92;

[0236] If it is determined that the value of the processing strategy flag is the second value, subsequent steps are stopped.

[0237] Regarding the apparatus in the above embodiments, the specific manner in which each module performs operations has been described in detail in the embodiments of the relevant methods and will not be elaborated on here.

[0238] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to the partial description of the method embodiments. The device embodiments described above are merely illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the disclosed solution. Those of ordinary skill in the art can understand and implement it without paying any creative work.

[0239] This specification also provides an electronic device, comprising:

[0240] processor;

[0241] a memory for storing processor-executable instructions;

[0242] The processor implements any of the above methods by running the executable instructions.

[0243] Figure 10 This is a schematic structural diagram of an electronic device provided by an exemplary embodiment. Figure 10 At the hardware level, the device includes a processor 1002, an internal bus 1004, a network interface 1006, a memory 1008, and a non-volatile memory 1010. Of course, it may also include hardware required for other services. One or more embodiments of this specification can be implemented based on software, such as the processor 1002 reading the corresponding computer program from the non-volatile memory 1010 into the memory 1008 and then running it. Of course, in addition to software implementation, one or more embodiments of this specification do not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc., that is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0244] Among them, as mentioned above Figure 8 and Figure 9 The device can be used for Figure 10 In the device shown, the technical solution as described above is implemented.

[0245] The devices, modules, or units described in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer, which may be in the form of a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email transceiver, game console, tablet computer, wearable device, or any combination of these devices.

[0246] In a typical configuration, a computer includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0247] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0248] This specification also provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of any of the above methods when executed by a processor.

[0249] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be used to store information using any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, disk storage, quantum memory, graphene-based storage media or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0250] Figure 11 1 is a schematic block diagram of an apparatus 1100 for acquiring advertisements according to an embodiment of the present disclosure. For example, apparatus 1100 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0251] Reference Figure 11 , device 1100 may include one or more of the following components: a processing component 1102 , a memory 1104 , a power component 1106 , a multimedia component 1108 , an audio component 1110 , an input / output (I / O) interface 1112 , a sensor component 1114 , and a communication component 1116 .

[0252] The processing component 1102 generally controls the overall operation of the device 1100, such as operations associated with display, phone calls, data communications, camera operation, and recording operations. The processing component 1102 may include one or more processors 1120 to execute instructions to perform all or part of the steps of the above-described method. In addition, the processing component 1102 may include one or more modules to facilitate interaction between the processing component 1102 and other components. For example, the processing component 1102 may include a multimedia module to facilitate interaction between the multimedia component 1108 and the processing component 1102.

[0253] The memory 1104 is configured to store various types of data to support the operation of the device 1100. Examples of such data include instructions for any application or method operating on the device 1100, contact data, phone book data, messages, pictures, videos, etc. The memory 1104 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0254] The power supply component 1106 provides power to the various components of the device 1100. The power supply component 1106 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device 1100.

[0255] The multimedia component 1108 includes a screen that provides an output interface between the device 1100 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, slides, and gestures on the touch panel. The touch sensor can not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 1108 includes a front camera and / or a rear camera. When the device 1100 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each front camera and rear camera can be a fixed optical lens system or have focal length and optical zoom capabilities.

[0256] The audio component 1110 is configured to output and / or input audio signals. For example, the audio component 1110 includes a microphone (MIC) that is configured to receive external audio signals when the device 1100 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal can be further stored in the memory 1104 or transmitted via the communication component 1116. In some embodiments, the audio component 1110 also includes a speaker for outputting audio signals.

[0257] I / O interface 1112 provides an interface between processing component 1102 and peripheral interface modules, such as a keyboard, click wheel, buttons, etc. These buttons may include but are not limited to: a home button, volume buttons, a start button, and a lock button.

[0258] Sensor assembly 1114 includes one or more sensors for providing various aspects of the status assessment of device 1100. For example, sensor assembly 1114 can detect the open / closed state of device 1100, the relative positioning of components, such as the display and keypad of device 1100. Sensor assembly 1114 can also detect changes in the position of device 1100 or a component of device 1100, the presence or absence of user contact with device 1100, the orientation or acceleration / deceleration of device 1100, and changes in the temperature of device 1100. Sensor assembly 1114 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 1114 can also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 1114 can also include an accelerometer, a gyroscope, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0259] The communication component 1116 is configured to facilitate wired or wireless communication between the device 1100 and other devices. The device 1100 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, 4G LTE, 5G NR or a combination thereof. In an exemplary embodiment, the communication component 1116 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 1116 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0260] In an exemplary embodiment, the device 1100 can be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the method described in any of the above embodiments.

[0261] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 1104 including instructions, and the instructions can be executed by the processor 1120 of the apparatus 1100 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0262] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the disclosure herein. This disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0263] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for obtaining advertisements, characterized in that: The method comprises: Obtaining evaluation results for at least one object category, wherein the evaluation results include user preference information for each object category; generating a target advertisement acquisition request carrying the evaluation result, and sending the target advertisement acquisition request to a server; A target advertisement set is obtained by the server in response to the target advertisement acquisition request and filtered based on the evaluation result.

2. The method for obtaining advertisements according to claim 1, wherein: The method further comprises: Acquiring object interaction information of a terminal, wherein the object interaction information includes interaction information between a user and each object on the terminal; The evaluation result is determined based on the object interaction information.

3. The method for obtaining advertisements according to claim 2, wherein: Determining the evaluation result based on the object interaction information includes: Processing the object interaction information according to a preset period to obtain the evaluation result; and / or, In a case where the object interaction information indicates that a preset interaction behavior occurs with at least one target object of the terminal, the object interaction information is processed to obtain the evaluation result.

4. The method for obtaining advertisements according to claim 1, wherein: The generating of the target advertisement acquisition request carrying the evaluation result includes: Obtain an original advertisement acquisition request for requesting an advertisement from a server; The target advertisement acquisition request is generated according to the original advertisement acquisition request, the processing strategy tag corresponding to the terminal, and the evaluation result, wherein the processing strategy tag is used to indicate whether the server needs to filter and obtain the target advertisement set based on the evaluation result.

5. The method for obtaining advertisements according to claim 1, wherein: The object includes at least one of the following: applications, products or services.

6. A method for pushing advertisements, characterized in that: The method comprises: Obtaining a target advertisement acquisition request from a terminal, wherein the target advertisement acquisition request carries an evaluation result, and the evaluation result includes preference information of a user of the terminal for each object category; In response to the target advertisement acquisition request, a target advertisement set is obtained by screening based on the evaluation result; Pushing the target advertisement set to the terminal.

7. The method for pushing advertisements according to claim 6, wherein: The step of screening and obtaining a target advertisement set based on the evaluation results includes: sorting all candidate advertisements according to the evaluation results to obtain sorting results corresponding to all candidate advertisements, wherein the candidate advertisements are advertisements used to promote candidate objects; According to the ranking result, a target advertisement is selected from all candidate advertisements; The target advertisement set including all the target advertisements is generated.

8. The method for pushing advertisements according to claim 7, characterized in that: Sorting all candidate advertisements according to the evaluation results to obtain ranking results corresponding to all candidate advertisements includes: Determining a terminal score corresponding to each candidate advertisement according to the evaluation result and the object category to which each candidate advertisement belongs; Determining an estimated advertising revenue corresponding to each candidate advertisement; Determining a final score corresponding to each candidate advertisement based on the terminal score corresponding to each candidate advertisement and the estimated advertising revenue corresponding to each candidate advertisement; All the candidate advertisements are sorted according to the final score corresponding to each candidate advertisement to obtain the sorting result.

9. The method for pushing advertisements according to claim 6, wherein: The method further comprises: Determining a processing strategy tag in the target advertisement acquisition request; If it is determined that the value of the processing strategy flag is the first value, executing a jump operation for jumping to the step of responding to the target advertisement acquisition request and obtaining target advertisement results based on the screening of the evaluation results; If it is determined that the value of the processing strategy flag is the second value, subsequent steps are stopped.

10. A device for obtaining advertisements, characterized in that: include: a first acquisition module, configured to acquire evaluation results of at least one object category, wherein the evaluation results include user preference information for each object category; A generating module, configured to generate a target advertisement acquisition request carrying the evaluation result, and send the target advertisement acquisition request to a server; The second acquisition module is configured to acquire a target advertisement set obtained by the server in response to the target advertisement acquisition request and screened based on the evaluation result.

11. The device for acquiring advertisements according to claim 10, characterized in that: Also includes: a third acquisition module, configured to acquire object interaction information of a terminal, wherein the object interaction information includes interaction information between a user and each object on the terminal; A result determination module is used to determine the evaluation result based on the object interaction information.

12. The device for acquiring advertisements according to claim 11, characterized in that: The result determination module is used for: Processing the object interaction information according to a preset period to obtain the evaluation result; and / or, In a case where the object interaction information indicates that a preset interaction behavior occurs with at least one target object of the terminal, the object interaction information is processed to obtain the evaluation result.

13. The device for acquiring advertisements according to claim 10, characterized in that: The generation module is used to: Obtain an original advertisement acquisition request for requesting an advertisement from a server; The target advertisement acquisition request is generated according to the original advertisement acquisition request, the processing strategy tag corresponding to the terminal, and the evaluation result, wherein the processing strategy tag is used to indicate whether the server needs to filter and obtain the target advertisement set based on the evaluation result.

14. A device for pushing advertisements, characterized in that: include: an acquisition module, configured to acquire a target advertisement acquisition request from a terminal, wherein the target advertisement acquisition request carries an evaluation result, and the evaluation result includes preference information of a user of the terminal for each object category; a screening module, configured to respond to the target advertisement acquisition request and screen a target advertisement set based on the evaluation result; A push module is used to push the target advertisement set to the terminal.

15. The device for pushing advertisements according to claim 14, characterized in that: The screening module includes: a ranking unit, configured to rank all candidate advertisements according to the evaluation result, and obtain ranking results corresponding to all candidate advertisements, wherein the candidate advertisements are advertisements for promoting candidate objects; a screening unit, configured to screen out a target advertisement from all the candidate advertisements according to the ranking result; The generating unit is configured to generate the target advertisement set including all the target advertisements.

16. The device for pushing advertisements according to claim 15, characterized in that: The sorting unit is used to: Determining a terminal score corresponding to each candidate advertisement according to the evaluation result and the object category to which each candidate advertisement belongs; Determining an estimated advertising revenue corresponding to each candidate advertisement; Determining a final score corresponding to each candidate advertisement based on the terminal score corresponding to each candidate advertisement and the estimated advertising revenue corresponding to each candidate advertisement; All the candidate advertisements are sorted according to the final score corresponding to each candidate advertisement to obtain the sorting result.

17. The device for pushing advertisements according to claim 14, wherein: The system further includes a judgment module, wherein the judgment module is used to: Determining a processing strategy tag in the target advertisement acquisition request; If it is determined that the value of the processing strategy flag is the first value, executing a jump operation for jumping to the step of responding to the target advertisement acquisition request and obtaining target advertisement results based on the screening of the evaluation results; If it is determined that the value of the processing strategy flag is the second value, subsequent steps are stopped.

18. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to implement the method according to any one of claims 1 to 9.

19. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

Images