Method and device for dynamically adjusting advertisement request sequence, equipment and medium

Abstract

The invention relates to a method and device for dynamically adjusting an advertisement request sequence, equipment and a medium, and the method comprises the steps: building and maintaining an advertisement space list, responding to a triggering operation of a user on advertisement content displayed on a target advertisement space, dynamically adjusting the sorting priority of one or more advertisement spaces, and according to the adjusted sorting priority, displaying the advertisement content on the target advertisement space. The list of advertising spaces is ranked to determine a sequence of requesting advertisements from an advertising platform. According to the method provided by the invention, real-time optimization of the advertisement request sequence is realized, the system can adaptively respond to user behavior changes, the advertisement putting accuracy is improved, and meanwhile, the technical means of controlling the priority to adjust the duration time through the preset time window is adopted, so that repeated requests of the same advertisement position are avoided in a short time, and the advertisement putting efficiency is improved. And each advertisement space can obtain fair display opportunities in a long time, so that reasonable distribution of system resources is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of computer advertising data processing, and in particular, to a method and device for dynamically adjusting an advertising request sequence, an apparatus, and a medium. BACKGROUND

[0002] With the vigorous development of mobile Internet advertising, in-app advertising has become a key means for many developers to monetize traffic. In the existing advertising technology architecture, Waterfall is a widely used advertising monetization strategy. Its basic logic is to sequentially request multiple advertising platforms in a preset, fixed priority order (usually based on the Effective Cost Per Mille (eCPM) value of the advertising platform) until an advertisement is successfully obtained and displayed.

[0003] However, to ensure click quality, advertising platforms will de-duplicate or determine as invalid repeated clicks by the same user within a short period of time. The existing system, due to the use of a fixed request sequence, cannot avoid requesting the same ad slot from the user again within a short period of time after the user clicks on a certain ad slot. The subsequent clicks generated by such repeated requests are extremely likely to be filtered by the platform side, resulting in a significant difference between the number of clicks recorded by the media side and the number of valid clicks recognized by the platform side. This not only causes direct loss of advertising revenue, but more importantly, this invalid repeated exposure occupies the traffic that could have been allocated to other high-quality ad slots, reducing overall monetization efficiency. SUMMARY

[0004] Therefore, it is necessary to provide a method, device, apparatus, and medium for dynamically adjusting an advertising request sequence, which can dynamically optimize the advertising request sequence and significantly improve the advertising monetization efficiency.

[0005] In a first aspect, the present application provides a method for dynamically adjusting an advertising request sequence, the method comprising:

[0006] establishing an ad slot list;

[0007] in response to a triggering operation of a user on an advertising content displayed on a target ad slot, dynamically adjusting the ranking priority of one or more ad slots;

[0008] sorting the ad slot list according to the adjusted ranking priority of the ad slots to determine a sequence for requesting advertisements from an advertising platform.

[0009] Further, the dynamic adjustment of the ranking priority of one or more ad slots comprises:

[0010] In response to a user's triggering action on the advertising content displayed on the target ad slot, the sorting priority of the target ad slot is changed within a subsequent preset time window, so that the target ad slot is placed later in the subsequent ad request sequence.

[0011] Furthermore, changing the sorting priority of the target ad slot includes:

[0012] Record the time when the triggering operation occurs;

[0013] Based on the occurrence time and the current time, the real-time ranking priority of the target ad slot is calculated and updated using a priority calculation function, wherein the priority calculation function is configured as follows:

[0014] When the time difference between the current time and the occurrence time is less than the deduplication time threshold, the original priority value of the target ad slot is added to the penalty value, and the penalized priority value is output.

[0015] When the time difference is greater than or equal to the deduplication time threshold, the original priority value is output.

[0016] Furthermore, the magnitude of the penalty value is configured to be sufficient to ensure that the penalized priority value is always lower than all unpenalized original priority values ​​in the sorting process.

[0017] Furthermore, the method also includes:

[0018] After determining the sequence of requesting advertisements from the advertising platform, an advertisement request is initiated to the advertising platform;

[0019] If an ad slot does not return valid ad content after a request is initiated, the ad slot will be excluded from the subsequent ad request sequence.

[0020] If multiple valid ad content are returned, the ad content identified as belonging to the preset e-commerce category will be displayed first.

[0021] Furthermore, the method also includes:

[0022] In response to receiving a manual configuration command, override the automatic sorting priority for a specific ad slot and set a fixed sorting position for that specific ad slot.

[0023] Furthermore, the method also includes:

[0024] The deduplication time threshold and / or the penalty value are dynamically set based on the historical click-through rate of the target ad placement or the user's historical behavior data.

[0025] Secondly, embodiments of the present invention provide an apparatus for dynamically adjusting an advertising request sequence, the apparatus comprising:

[0026] Create a module for building a list of ad slots;

[0027] The response module is used to respond to user actions that trigger the display of ad content on the target ad slot, and dynamically adjust the sorting priority of one or more ad slots.

[0028] The request module is used to sort the list of ad slots according to the adjusted sorting priority of the ad slots to determine the sequence of requests for ads to the ad platform.

[0029] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in any one of the first aspects.

[0030] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described in any one of the first aspects.

[0031] The above-mentioned method, apparatus, device, and medium for dynamically adjusting the sequence of ad requests achieve intelligent allocation of ad traffic by establishing a list of ad slots, responding to user clicks and dynamically adjusting priorities based on time windows and priority calculation functions, and then reordering the request sequence. Therefore, this invention achieves real-time optimization of the ad request sequence by establishing an ad slot list and dynamically adjusting the sorting priority based on user-triggered operations. This enables the system to adaptively respond to changes in user behavior, improving the accuracy of ad delivery. The use of a preset time window to control the duration of priority adjustment ensures that duplicate requests for the same ad slot are avoided in the short term, while guaranteeing fair display opportunities for all ad slots in the long term, achieving a reasonable allocation of system resources. By recording the trigger time and combining it with a priority calculation function based on penalty values, a quantitative ad slot evaluation mechanism is provided, enabling the system to objectively and consistently execute sorting decisions, improving the stability and reliability of system operation. Setting dynamically adjustable deduplication time thresholds and penalty values ​​allows the system to adaptively optimize based on the characteristics of different ad slots and user behavior patterns, improving the system's adaptability and effectiveness in different application scenarios. By excluding invalid ad slots and prioritizing the display of e-commerce ads, the invention effectively improves ad fill rate and display quality, reduces system resource waste, and improves ad monetization efficiency. The provision of a manual configuration interface allows for manual intervention in special scenarios while maintaining automated system operation, enhancing the system's flexibility and practicality. Attached Figure Description

[0032] Figure 1 These are internal structural diagrams of the computer device in some embodiments;

[0033] Figure 2 This is one of the flowcharts illustrating a method for dynamically adjusting the sequence of ad requests in some embodiments;

[0034] Figure 3 This is a schematic diagram illustrating the process of initiating an advertising request to an advertising platform in some embodiments;

[0035] Figure 4 This is a second flowchart illustrating a method for dynamically adjusting the sequence of ad requests in some embodiments;

[0036] Figure 5 This is a schematic diagram of the framework of a device for dynamically adjusting the sequence of advertising requests in some embodiments. Detailed Implementation

[0037] In the embodiments of this application, the term "and / or" describes the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following associated objects have an "or" relationship.

[0038] In the embodiments of this application, the term "multiple" refers to two or more, and other quantifiers are similar.

[0039] In the embodiments of this application, the term "at least one" means one or more. For example, at least one of A, B and C can represent six situations: A exists alone, B exists alone, C exists alone, A and B exist simultaneously, A and C exist simultaneously, B and C exist simultaneously, and A, B and C exist simultaneously.

[0040] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0041] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0042] In some embodiments, the method for dynamically adjusting the ad request sequence provided in this application can be deployed in a client device. This client device, as the terminal execution unit for ad display, is responsible for processing user interaction behavior and optimizing ad request strategies in real time. Specifically, it can run in client environments such as mobile terminals, tablet devices, or personal computers to meet the low-latency requirements of real-time user interaction.

[0043] The client device comprises complete hardware components: a processor, serving as the computing core, is responsible for performing key calculations such as ad placement priority calculation and sorting sequence generation; the memory includes non-volatile storage media and internal memory, which stores the operating system and the computer program implementing this method; the input / output interface is responsible for data interaction between the processor and user interaction devices such as touchscreens and sensors; the communication interface supports establishing connections with the advertising platform server via WIFI and mobile cellular networks, sending ad requests, and receiving ad content; the display unit is used to render and display ad content; and the input device is used to receive user clicks, swipes, and other trigger operations.

[0044] In actual operation, through the collaborative work of various hardware components, the system can maintain the status of the ad slot list locally on the client side, monitor user actions triggered by ad content in real time, and dynamically adjust the ad slot sorting priority based on a preset algorithm. By using local client-side computation, communication latency with the server is effectively reduced, improving the response speed of personalized ad requests. Especially when handling high-frequency user interaction scenarios, local caching and pre-computation mechanisms significantly improve the efficiency of ad request sequence updates.

[0045] In terms of system architecture, a hybrid processing mode can be adopted: tasks with high real-time requirements, such as ad slot status maintenance and priority calculation, are deployed on the client side for execution, while resource-intensive tasks such as ad content acquisition and historical data analysis are still handled on the server side. This architecture ensures both immediate response to user interactions and computational efficiency for large-scale data processing. Those skilled in the art will understand that... Figure 1 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0046] In some embodiments, such as Figure 2 As shown, a method for dynamically adjusting the ad request sequence is provided, which can be applied to... Figure 1 Taking a computer device as an example, the explanation includes the following steps:

[0047] S201, Create a list of ad slots.

[0048] The ad placement list is a dynamic data structure created in the client's memory. Each list item is an object containing attributes such as ad placement identifier, original priority, and last trigger timestamp. The ad placement identifier uniquely identifies an ad placement, such as "p1" or "p2". The original priority is a preset value reflecting the basic value of the ad placement (e.g., based on eCPM estimation) and usually remains unchanged after list initialization. The last trigger timestamp records the time of the user's last click on this ad placement. The initial value is 0 (or null), indicating no click.

[0049] The setup process occurs during user session initialization, where the system retrieves ad placement configuration metadata from the server and instantiates ad placement objects locally to form an initial list. The maintenance process is an automated state management process that continues throughout system operation, including updating the last trigger timestamp of ad placements and removing ad placements from the list when a request fails.

[0050] In some embodiments, during the setup phase, the system can dynamically calculate the personalized initial priority of each ad slot based on user profile characteristics and real-time environmental information using a locally running lightweight machine learning model, achieving differentiated list initialization based on user interest tags, network environment, and other characteristics. During the maintenance phase, the system can implement a self-repair mechanism for list health, including setting timers to periodically revive removed ad slots and a performance evaluation mechanism that triggers list reconstruction based on metrics such as fill rate. This transforms the ad slot list from a static configuration into an intelligent management module with self-learning and adaptive capabilities. Through the synergistic effect of personalized initialization and dynamic maintenance mechanisms, the overall performance and robustness of the ad request system are improved.

[0051] S202, in response to a user's triggering action on the advertising content displayed on the target ad slot, dynamically adjust the sorting priority of one or more ad slots.

[0052] In this step, the target ad placement specifically refers to the ad display location where the user actually triggers an action; it is a specific entry in the ad placement list. Its identifier is used to precisely locate the ad placement object that needs adjustment within the list. Triggering actions include, but are not limited to, user interactions such as clicks, long presses, and swipes. The system captures these actions by listening to event callbacks from the ad container component and records the action type and timestamp. Dynamic adjustment refers to the automated process by which the system automatically recalculates ad placement priorities based on a preset algorithm and real-time user interactions. This process breaks the limitations of traditional static sorting and achieves intelligent decision-making based on real-time feedback.

[0053] Step S202 establishes an intelligent dynamic priority adjustment mechanism to achieve real-time optimization of the ad request sequence. The core of this step lies in responding to user actions triggered on the target ad placement. A multi-dimensional perception system accurately captures different types of interactive behaviors, including clicks, long presses, and swipes, and records precise timestamp information. The system then activates the priority calculation engine, recalculating the ad placement's ranking priority based on a preset algorithm combined with parameters such as the current system time, the last trigger timestamp, and the original priority. The updated priority is then synchronized to the ad placement list in real time.

[0054] In implementation, the front-end advertising SDK captures user interaction events with ad placements through an event listener mechanism, obtaining the target ad placement ID and operation timestamp. Based on the captured events, it updates the last triggered timestamp field of the corresponding ad placement in the ad placement list. It then calls the priority calculation engine, combining the current system time, last triggered timestamp, and original priority parameters to execute a priority algorithm. Finally, it updates the corresponding field of the ad placement object with the calculated new priority, completing this dynamic adjustment.

[0055] In some embodiments of the present invention, this can also be achieved in the following ways: First, by establishing a differentiated response mechanism based on trigger type, the system can distinguish the user intent behind different interactive behaviors and implement precise priority adjustment strategies. Second, the collaborative adjustment mechanism can synchronously adjust the priority of related ad slots based on the semantic correlation between ad slots when a single ad slot is triggered, forming an intelligent ad recommendation network. Furthermore, the lightweight neural network model deployed on the client can output the optimal adjustment parameters in real time based on user characteristics and context, achieving truly personalized priority adjustment. Finally, by establishing a real-time effect feedback loop, the system can continuously evaluate the adjustment effect and dynamically optimize strategy parameters to ensure long-term operational effectiveness.

[0056] S203, Sort the list of ad slots according to the adjusted sorting priority to determine the sequence of requests for ads to the ad platform.

[0057] The adjusted sorting priority refers to the numerical weighting index obtained after dynamic adjustment in step S202. This index comprehensively considers multiple dimensions such as the basic value of the ad slot and real-time user interaction behavior, and is the core basis for determining the request order. The ad request sequence is an ordered ad slot queue generated based on the adjusted sorting priority. This sequence determines the order in which requests are sent to the ad platform and is a key bridge connecting priority calculation and ad acquisition.

[0058] In some embodiments, step S203 transforms the dynamically adjusted priorities into an optimized ad request sequence through an intelligent sorting mechanism. This step first performs a rapid sorting of the real-time priority in the ad slot list, generating a request queue arranged in descending order of priority to ensure that high-value ad slots receive priority request opportunities. In the basic implementation, the system uses an efficient sorting algorithm to process the priority data and initiates ordered requests to the ad platform according to the generated sequence.

[0059] Alternatively, a ranking model based on multi-objective programming can be established, simultaneously considering multiple optimization objectives such as expected revenue, user experience, and ad diversity. Pareto optimality can then be used to generate a request sequence that balances the interests of all parties. This overcomes the limitations of a single priority indicator, achieving comprehensive optimization of the ad request sequence and improving long-term revenue and user satisfaction.

[0060] Alternatively, a real-time context-aware module can be introduced to dynamically adjust the sorting strategy based on environmental factors such as network status and device performance. For example, in a weak network environment, priority could be given to ad slots that load quickly. This enhances the system's adaptability to environmental changes and ensures excellent performance across various usage scenarios.

[0061] Alternatively, a lightweight reinforcement learning model can be deployed, using historical request performance as a reward signal to continuously optimize the ranking strategy. Algorithms such as Q-learning can be used to learn the optimal sequence generation strategy. This enables the system to learn autonomously from historical experience, gradually improving the quality and effectiveness of sequence generation.

[0062] In some embodiments, dynamically adjusting the sorting priority of one or more ad slots includes: in response to a user's triggering operation on the ad content displayed on the target ad slot, changing the sorting priority of the target ad slot within a subsequent preset time window, so that the target ad slot is placed later in the subsequent ad request sequence.

[0063] In some embodiments, this technical solution achieves intelligent adjustment of ad placement priority by establishing a dynamic penalty mechanism based on a time window. Specifically, when the system detects a user's triggering action on a specific ad placement, a countdown window (e.g., 60 seconds) is initiated. During the duration of this window, the system automatically reduces the ranking weight of the target ad placement through an algorithm. The advantage of this approach is that its core purpose is to significantly improve the user experience within the application. When a user becomes interested in an ad and performs a triggering action (e.g., clicks), their typical behavioral intention is usually to gain a deeper understanding of the ad content or complete the corresponding conversion process. If the user returns to the original application interface shortly after performing the action, and the same ad placement is immediately filled with and displays a new ad, it will create unnecessary interference and even increase the risk of accidental touches, thereby leading to interruption of the user experience and a decrease in satisfaction. By actively reducing the ranking priority of the target ad placement within the preset time window defined in this invention, the system essentially creates an ad display cooling-off period for it. During this period, the probability of the ad placement being requested and displaying a new ad is greatly reduced, thereby effectively avoiding the aforementioned interference, ensuring a smooth transition for users from ad interaction back to the main application process, and fundamentally optimizing the human-computer interaction experience.

[0064] Furthermore, this approach optimizes overall ad placement effectiveness and monetization efficiency. From an ad performance perspective, after a user has just interacted with an ad, their attention is partially occupied, and immediately displaying a new ad in the same spot typically results in a lower expected click-through rate. By temporarily shifting the request order of that ad placement, the system can allocate valuable first-request opportunities to other ad placements more likely to attract user attention and clicks, thereby improving the overall click-through rate and fill quality of app ads. Simultaneously, this strategy helps prevent overexposure and ad fatigue to users in the same ad placement, maintaining user sensitivity and acceptance of ad content, which is crucial for the long-term health of app monetization.

[0065] Therefore, by establishing a dynamic relationship between triggering operations and ranking weights, the system can autonomously adapt to changes in user behavior and achieve personalized optimization of ad display. The introduction of the time window mechanism ensures that the system maintains a balance between short-term suppression and long-term fairness, while the configurable parameter system provides a technical foundation for refined operations in different business scenarios. This dynamic adjustment mechanism ultimately enables the ad request sequence to intelligently adapt to changes in users' real-time interests, thereby comprehensively improving ad delivery effectiveness and user experience.

[0066] In some embodiments, changing the sorting priority of a target ad placement includes: recording the occurrence time of the triggering operation; calculating and updating the real-time sorting priority of the target ad placement based on the occurrence time and the current time using a priority calculation function, wherein the priority calculation function is configured as follows:

[0067] When the time difference between the current time and the occurrence time is less than the deduplication time threshold, the original priority value of the target ad slot is added to the penalty value, and the penalized priority value is output.

[0068] When the time difference is greater than or equal to the deduplication time threshold, the original priority value is output.

[0069] In other words, the specific process of changing the ranking priority of the target ad slot includes the following technical details: The system first records the time when the triggering operation occurs, and this timestamp serves as the base parameter for priority calculation. Subsequently, the system obtains the current time, calculates the time difference between the current time and the occurrence time, and inputs this time difference into the priority calculation function.

[0070] The priority calculation function performs branch calculations according to preset rules: when the time difference is less than the deduplication time threshold, the function adds the original priority value of the target ad slot to the penalty value and outputs the penalized priority value; when the time difference is greater than or equal to the deduplication time threshold, the function directly outputs the original priority value.

[0071] This technical solution achieves automated adjustment of sorting priority through precise time difference calculation and function-based priority calculation. The comparison between the time difference and the deduplication time threshold ensures the timeliness of priority adjustment, while the addition of penalty values ​​provides a quantifiable priority adjustment mechanism. The entire calculation process, through rigorous logical judgment and mathematical operations, guarantees the accuracy and consistency of priority adjustment.

[0072] For example: Suppose that the original priority value of an ad slot "Ad Slot A" is 100, the deduplication time threshold set by the system is 60 seconds, and the penalty value is 10000.

[0073] When a user triggers the ad slot at 14:30:00, the system records this time as the occurrence time. If a new request is initiated at 14:30:25 (a time difference of 25 seconds), since 25 seconds is less than the 60-second threshold, the system performs a penalty calculation: 100 + 10000 = 10100, and outputs the penalized priority value. At this point, the ad slot receives an extremely high priority value and is automatically moved to the end of the subsequent request sequence.

[0074] If a request is initiated at 14:31:30 (a time difference of 90 seconds), because 90 seconds exceeds the 60-second threshold, the system directly outputs the original priority value of 100, and the ad slot is restored to its normal sorting position. This mechanism ensures, through quantitative mathematical calculations, that the triggered ad slot is effectively removed from the priority display queue within the set time window, achieving precise deduplication control.

[0075] In some embodiments, the deduplication time threshold and / or penalty value are dynamically set based on the historical click-through rate of the target ad placement or the user's historical behavior data.

[0076] The system dynamically adjusts the deduplication time threshold and penalty value by analyzing the historical click-through rate (CTR) data of the target ad placements. Specifically, for high-quality ad placements with high historical CTR, the system configures a shorter deduplication time threshold and a smaller penalty value to reduce the risk of misjudgment; while for ad placements with low historical CTR, a longer deduplication time threshold and a larger penalty value are used to enhance the control effect.

[0077] Meanwhile, the system personalizes parameter settings based on users' historical behavioral characteristics. For users with frequent clicks, the system automatically increases the penalty value and extends the deduplication time threshold; while for users with normal behavior, standard parameter settings are used. This data-driven dynamic parameter adjustment mechanism enables the system to implement precise strategy control for different ad placement qualities and user behavior characteristics, optimizing user experience while ensuring advertising effectiveness.

[0078] The following is an example of dynamic settings based on the historical click-through rate (CTR) of a target ad placement: Assume the system detects that the historical CTR of "Ad Placement A" is consistently at a high level of 5%. Therefore, the deduplication time threshold is dynamically set to 30 seconds, and the penalty value is 5000. If a user triggers this ad placement at 14:30:00, and then initiates a new request at 14:30:25, the system will perform a priority calculation of 100 + 5000 = 5100. At this point, the ad placement will move down in the ranking, but due to the appropriate penalty value, it will still maintain a position superior to lower-quality ad placements, thus ensuring reasonable exposure opportunities for high-quality ad placements while achieving necessary deduplication.

[0079] Dynamic settings based on user historical behavior data exhibit different characteristics: when the system identifies a user with high-frequency clicking characteristics, it automatically extends the deduplication time threshold to 90 seconds and increases the penalty value to 20,000. Similarly, if a request is initiated 25 seconds after triggering the ad slot, the system will perform a priority calculation of 100 + 20,000 = 20,100. At this time, the ad slot will receive an extremely high priority value, ensuring that it is always at the end of the subsequent request sequence, thereby achieving strict control over abnormal user behavior.

[0080] In some embodiments, the penalty value is configured to be large enough to ensure that the penalized priority value is always lower than all unpenalized original priority values ​​in the sorting process.

[0081] In other words, the configuration of the penalty value follows the core principle of ensuring the effectiveness of the ranking. This technical solution mathematically guarantees that the penalized priority value is always lower than the original, unpenalized priority value. This approach ensures the ranking results are clear and reliable. By setting the penalty value to a sufficiently large amount, ensuring that the penalized priority value is always lower than the original priority value, it completely avoids situations where penalized ad placements remain in a high ranking position due to insufficient penalty. This guarantees that each triggered operation leads to a deterministic adjustment of the ad placement sequence, thereby strengthening the actual effectiveness of ad deduplication and user experience protection mechanisms.

[0082] The specific implementation is based on the following mathematical relationship: Let P_max be the maximum original priority of all ad slots in the system, and P_penalty be the penalty value. When the penalty value satisfies P_penalty > P_max, for any ad slot, its penalized priority value (original priority value + P_penalty) will be greater than P_max. Since the sorting rules are usually arranged in descending order of priority, a larger value corresponds to a lower sorting position, thus ensuring that penalized ad slots are always placed after all normal ad slots.

[0083] For example, if there are three ad slots in the system with original priorities of 200, 150, and 100 (P_max = 200), and a penalty value configured as 10000, when an ad slot is penalized, its priority value becomes 10200, 10150, or 10100. These values ​​are all greater than 200, and in descending order, they naturally appear after all normal ad slots. This configuration method mathematically ensures the absolute reliability of the sorting logic, avoiding sorting anomalies caused by overlapping priority value ranges.

[0084] In some embodiments, such as Figure 3 As shown, the method for dynamically adjusting the ad request sequence may further include the following steps:

[0085] S204: After determining the sequence of requests for advertisements from the advertising platform, an advertisement request is sent to the advertising platform.

[0086] Step S204 is the execution stage in the ad request process. After completing the sorting logic of the ad request sequence, this step actually initiates the data interaction process with the ad platform. Specifically, the system transforms the determined ad request sequence into specific network requests and initiates calls to the ad platform's service interface according to the sequence order.

[0087] S205, determine whether the ad slot returns valid ad content after the request is initiated. If not, proceed to step S206; if yes, proceed to step S207.

[0088] Step S205 is the decision-making stage in the ad response processing flow. After initiating an ad request, this step verifies the validity of the content returned by the ad platform and executes different branch processes based on the verification result. Specifically, the system parses the ad platform's response data to determine whether it contains valid ad content that meets display standards. This judgment process constitutes the branch conditions for subsequent steps S206 and S207, and is the fundamental decision-making node for achieving ad fill rate optimization and intelligent content display.

[0089] S206 If the ad slot does not return valid ad content after the request is initiated, the ad slot shall be excluded from the subsequent ad request sequence.

[0090] Step S206 implements a dynamic optimization mechanism for the ad request sequence. When an ad slot fails to return valid ad content, this step automatically excludes that ad slot from the subsequent ad request sequence. This real-time filtering mechanism optimizes request efficiency by removing invalid ad slots, ensuring that subsequent requests are concentrated on ad slots with actual fill capacity, thereby significantly improving the overall ad fill rate and system resource utilization. This technical solution establishes an adaptive request sequence maintenance system that continuously removes invalid nodes to maintain the optimal state of the sequence.

[0091] S207 If multiple valid ad content are returned, the ad content identified as belonging to the preset e-commerce category will be displayed first.

[0092] Step S207 implements an intelligent display strategy for scenarios with multiple ad content. When the system receives multiple valid ad contents, this step prioritizes displaying ad content categorized into preset e-commerce categories through a content recognition mechanism. This display optimization mechanism, based on semantic analysis and classification of ad content, establishes a set of priority display rules based on ad type. This technical solution ensures that high-value e-commerce ads receive priority exposure through intelligent filtering, thereby effectively improving the overall monetization efficiency and commercial value of ad placements.

[0093] In the ad request and decision-making process, steps S205 to S207 together construct an efficient and revenue-driven closed-loop mechanism. This process begins with sequential requests for ad slots A, B, and C in a preset ad slot sequence. The system first requests ad slot A, which is at the top of the list, but the ad platform returns a response indicating no ad is filled. At this point, S205, acting as the decision-making hub, quickly assesses the validity of this result and triggers S206 to execute exclusion logic, immediately removing ad slot A from the list and updating the current list to ad slots B and C. This operation significantly optimizes subsequent request paths and improves overall filling efficiency.

[0094] Subsequently, the system continued to request ad slot B, and the advertising platform returned a valid video ad. S205 again verified its validity and recorded the request as successful. The system then continued to request ad slot C, again receiving a valid e-commerce ad response. At this point, the system held two valid ad contents simultaneously, and the display optimization logic in S207 was activated: the system identified that the ad returned by ad slot C belonged to the preset e-commerce category. Although ad slot B was earlier in the original sequence, the system still prioritized displaying the e-commerce ad based on business rules. The core of this "preferred selection" strategy lies in identifying the potential value of different types of ads. E-commerce ads are prioritized because they typically have higher conversion rates and monetization value, thereby maximizing the revenue from a single ad exposure.

[0095] In some embodiments of the present invention, such as Figure 4 As shown, the method for dynamically adjusting the ad request sequence may further include the following steps:

[0096] S208, in response to receiving a manual configuration instruction, overrides the automatic sorting priority for a specific ad slot and sets a fixed sorting position for that specific ad slot.

[0097] In this step, the automatic sorting priority can be derived from the dynamic adjustment mechanism defined in the foregoing embodiments of this invention. Specifically, it is a real-time sorting priority calculated by the system in response to a user's triggering action on an advertisement (such as clicking), based on the time difference between the triggering action and the current time, using a predefined priority calculation function. This mechanism aims to achieve ad deduplication and user experience optimization by temporarily reducing the priority of already interacted ad slots.

[0098] It can also be any other automated ranking logic in the system based on algorithms or data. For example, it can be a priority calculated based on the historical performance data of the ad placement (such as historical click-through rate (CTR) and historical revenue per thousand impressions (eCPM), or a priority predicted by a machine learning model based on contextual information (such as user profiles and application content).

[0099] Step S208 provides a manual intervention mechanism within the automated system. This step, by receiving external manual configuration commands, enables the overriding of automatic sorting priorities for specific ad slots. Upon receiving the configuration command, the system temporarily suspends the automated sorting algorithm for the specified ad slot and instead adopts a manually set fixed sorting position. This design, while maintaining the system's automated operation, provides a flexible intervention method for strategy adjustments in special scenarios, ensuring a balance between algorithmic decision-making and human experience.

[0100] For example, suppose the system automatically calculates that "Ad Slot B" has a real-time ranking priority of 150, which, according to the algorithm, should be ranked third. The operations staff sends a manual configuration command to the system through the management backend, specifying that "Ad Slot B" should be permanently ranked first. Upon receiving this command, the system immediately overwrites the original automatic ranking result, fixing the ranking position of "Ad Slot B" at 1. Thereafter, regardless of any changes in the automatic ranking priority of "Ad Slot B," it will maintain its first position in the subsequent ad request sequence until a new configuration command is received. This mechanism allows operations staff to temporarily increase the display priority of specific ad slots during promotional activities or to fix the display position of an ad slot during the testing phase.

[0101] Based on the same inventive concept, this application also provides an apparatus for dynamically adjusting an ad request sequence. The solution provided by this apparatus is similar to the solution described in the above-described method. Therefore, the specific limitations of one or more apparatus embodiments for dynamically adjusting an ad request sequence provided below can be found in the limitations of the method for dynamically adjusting an ad request sequence described above, and will not be repeated here.

[0102] In some embodiments, such as Figure 5 As shown, an apparatus for dynamically adjusting the sequence of ad requests is provided, comprising:

[0103] Module 21 is used to create a list of ad slots.

[0104] The response module 22 is used to dynamically adjust the sorting priority of one or more ad slots in response to user actions that trigger the display of ad content on the target ad slot.

[0105] The request module 23 is used to sort the list of ad slots according to the adjusted sorting priority to determine the sequence of requests for ads to the ad platform.

[0106] In some embodiments, the response module 22 dynamically adjusts the sorting priority of one or more ad slots, including:

[0107] In response to a user's triggering action on the advertising content displayed on the target ad slot, the sorting priority of the target ad slot is changed within a subsequent preset time window, so that the target ad slot is placed later in the subsequent ad request sequence.

[0108] In some embodiments, the response module 22 changes the sorting priority of the target ad slot, including:

[0109] Record the time when the triggering operation occurs;

[0110] Based on the occurrence time and the current time, the real-time ranking priority of the target ad slot is output using a priority calculation function, wherein the priority calculation function is configured as follows:

[0111] When the time difference between the current time and the occurrence time is less than the deduplication time threshold, the original priority value of the target ad slot is added to the penalty value, and the penalized priority value is output.

[0112] When the time difference is greater than or equal to the deduplication time threshold, the original priority value is output.

[0113] In some embodiments, the penalty value is configured to be large enough to ensure that the penalized priority value is always lower than all unpenalized original priority values ​​in the sorting process.

[0114] In some embodiments, the apparatus may further include:

[0115] Request initiation module 24 is used to initiate an advertising request to the advertising platform after the sequence of requesting advertising from the advertising platform is determined;

[0116] The first execution module 25 is used to exclude the ad slot from the subsequent ad request sequence if the ad slot does not return valid ad content after the request is initiated.

[0117] The second execution module 26 is used to prioritize displaying the advertising content identified as belonging to the preset e-commerce category if multiple valid advertising contents are returned.

[0118] In some embodiments, the apparatus further includes a manual configuration module 27, which, in response to receiving a manual configuration instruction, overrides the automatic sorting priority for a specific ad slot and sets a fixed sorting position for that specific ad slot.

[0119] In some embodiments, the deduplication time threshold and / or the penalty value are dynamically set based on the historical click-through rate of the target ad placement or the user's historical behavior data.

[0120] Each module in the aforementioned device for dynamically adjusting the ad request sequence can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0121] In some embodiments, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method for dynamically adjusting the advertising request sequence as described in any of the above embodiments.

[0122] In some embodiments, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for dynamically adjusting the advertising request sequence as described in any of the above embodiments.

[0123] In some embodiments, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the method for dynamically adjusting the advertising request sequence as described in any of the above embodiments.

[0124] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0125] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0126] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for dynamically adjusting the sequence of advertising requests, characterized in that, The method includes: Create a list of ad placements; In response to user actions that trigger the display of ad content on the target ad slot, dynamically adjust the sorting priority of one or more ad slots; The list of ad slots is sorted according to the adjusted priority of the ad slots to determine the sequence of ad requests to the ad platform.

2. The method according to claim 1, characterized in that, The dynamic adjustment of the sorting priority of one or more ad slots includes: In response to a user's triggering action on the advertising content displayed on the target ad slot, the sorting priority of the target ad slot is changed within a subsequent preset time window, so that the target ad slot is placed later in the subsequent ad request sequence.

3. The method according to claim 2, characterized in that, The change in the sorting priority of the target ad slot includes: Record the time when the triggering operation occurs; Based on the occurrence time and the current time, the real-time ranking priority of the target ad slot is calculated and updated using a priority calculation function, wherein the priority calculation function is configured as follows: When the time difference between the current time and the occurrence time is less than the deduplication time threshold, the original priority value of the target ad slot is added to the penalty value, and the penalized priority value is output. When the time difference is greater than or equal to the deduplication time threshold, the original priority value is output.

4. The method according to claim 3, characterized in that, The penalty value is configured to be large enough to ensure that the penalized priority value is always lower than all the original, unpenalized priority values ​​in the sorting process.

5. The method according to claim 1, characterized in that, The method further includes: After determining the sequence of requesting advertisements from the advertising platform, an advertisement request is initiated to the advertising platform; If an ad slot does not return valid ad content after a request is initiated, the ad slot will be excluded from the subsequent ad request sequence. If multiple valid ad content are returned, the ad content identified as belonging to the preset e-commerce category will be displayed first.

6. The method according to claim 1, characterized in that, The method further includes: In response to a received manual configuration command, override the automatic sorting priority for a specific ad slot and set a fixed sorting position for that specific ad slot.

7. The method according to claim 3, characterized in that, The method further includes: The deduplication time threshold and / or the penalty value are dynamically set based on the historical click-through rate of the target ad placement or the user's historical behavior data.

8. An apparatus for dynamically adjusting the sequence of advertising requests, characterized in that, The device includes: Create a module for building a list of ad slots; The response module is used to respond to user actions that trigger the display of ad content on the target ad slot, and dynamically adjust the sorting priority of one or more ad slots. The request module is used to sort the list of ad slots according to the adjusted sorting priority of the ad slots to determine the sequence of requests for ads to the ad platform.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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