Interaction sensitivity adjusting method, system and device, equipment and medium

Abstract

The invention relates to an interaction sensitivity adjusting method, system and device, equipment and medium, and the method applied to a server side comprises the steps: when an advertisement request sent by a client side of target equipment is received, sending advertisement data matched with the advertisement request to the client side, so that the client side displays the advertisement content in the advertisement data; receiving at least one piece of user behavior data returned by the client within a preset time period to obtain a behavior data set; calculating an actual click rate of the target device in a preset time period according to the behavior data set; and calculating a target sensitivity threshold by using the actual click rate and the expected click rate, and replacing the initial sensitivity threshold with the target sensitivity threshold to adjust the equipment interaction sensitivity of the server type. The problem that the interaction sensitivity of the device to the user cannot meet the user experience is solved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method, system, device, equipment and medium for adjusting interaction sensitivity. Background Art

[0002] In Internet APPs, in addition to the common click and slide interaction methods, there are also some special interaction methods, such as "shake" and "twist", which are designed to provide a richer and more interesting user experience. These interesting interaction methods are achieved by collecting some sensor parameters of the device system (for example, acceleration, gravity sensing, etc.). When the user shakes the phone so that these sensing parameters meet certain threshold conditions, it is determined that the user triggers the interaction behavior, and then the APP performs corresponding interaction processing. The threshold condition here refers to the sensitivity parameter of shaking or twisting. The sensitivity parameter is generally tested repeatedly in the early stage, and the final value is finally determined based on the expected click rate and user experience.

[0003] However, for the same sensitivity threshold parameters, the sensitivity perceived by users on different device manufacturers or different models varies greatly. Some users feel that the shaking function is particularly insensitive, while some users feel that it is too sensitive. They may accidentally twist the device and trigger the jump of the interactive interface. This results in the device's interactive sensitivity to users not being able to meet the user experience.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The present application provides a method, system, device, equipment and medium for adjusting interaction sensitivity to solve the above-mentioned technical problem that "the interaction sensitivity of the device to the user cannot meet the user experience".

[0006] According to one aspect of an embodiment of the present application, the present application provides a method for adjusting interaction sensitivity, which is applied to a server, and includes: whenever an advertising request is received from a client of a target device, sending advertising data matching the advertising request to the client, so that the client displays the advertising content in the advertising data, wherein the advertising data includes the advertising content and an initial sensitivity threshold of the target device; receiving at least one user behavior data returned by the client within a preset time period to obtain a behavior data set, wherein the user behavior data is obtained by the client by monitoring whether the user triggers an interaction behavior on the target device, and whether the interaction behavior is triggered is determined based on the initial sensitivity threshold; calculating the actual click-through rate of the target device in the preset time period according to the behavior data set; calculating the target sensitivity threshold using the actual click-through rate and the expected click-through rate, and replacing the initial sensitivity threshold with the target sensitivity threshold to adjust the device interaction sensitivity of the server model.

[0007] Optionally, the actual click-through rate of the target device in a preset time period is calculated based on the behavior data set, including: counting a first number of user behavior data in the behavior data set, and taking the first number as the exposure number; extracting a detection result from each user behavior data, wherein the detection result is used to indicate that the user has triggered the target operation or the user has not triggered the target operation; counting the number of detection results indicating that the user has triggered the target operation to obtain a second number, and taking the second number as the click number; calculating the ratio of the click number to the exposure number, and determining the ratio as the actual click-through rate of the target device in the preset time period.

[0008] Optionally, the target sensitivity threshold is calculated using the actual click rate and the expected click rate, including: subtracting the expected click rate from the actual click rate to obtain the difference; if the difference is greater than 0, adding the initial sensitivity threshold to the preset step value to obtain the target sensitivity threshold; if the difference is less than 0, subtracting the preset step value from the initial sensitivity threshold to obtain the target sensitivity threshold; if the difference is equal to 0, using the initial sensitivity threshold as the target sensitivity threshold.

[0009] According to another aspect of an embodiment of the present application, the present application provides a method for adjusting interaction sensitivity, which is applied to a client, and includes: sending an advertising request to a server, wherein the advertising request carries the server model of a target device; receiving advertising data returned by the server, and displaying the advertising content in the advertising data; extracting an initial sensitivity threshold from the advertising data, and using the initial sensitivity threshold to monitor the user's interaction behavior triggered by the advertising content to obtain user behavior data; sending the user behavior data to the client, so that the client calculates the target sensitivity threshold based on the user behavior data to adjust the device interaction sensitivity.

[0010] Optionally, an initial sensitivity threshold is used to monitor the user's interactive behavior triggered by the advertising content to obtain user behavior data, including: detecting whether the user has triggered an interactive behavior in response to the advertising content, wherein the interactive behavior includes clicking behavior and shaking behavior; in the process of displaying the advertising content, if it is detected that the user has triggered an interactive behavior in response to the advertising content, then the user triggering a target operation is taken as the detection result; if it is not detected that the user has triggered an interactive behavior in response to the advertising content, then the user not triggering the target operation is taken as the detection result; and the detection result is taken as the user behavior data.

[0011] According to another aspect of an embodiment of the present application, the present application provides a system for adjusting interaction sensitivity, the system including a server and a client, wherein the client is used to send an advertisement request to the server, wherein the advertisement request carries the server model of the target device; receive advertisement data returned by the server, and display the advertisement content in the advertisement data, wherein the advertisement data includes the advertisement content and the initial sensitivity threshold of the target device; extract the initial sensitivity threshold from the advertisement data, and use the initial sensitivity threshold to monitor the user's interaction behavior triggered by the advertisement content to obtain user behavior data; send the user behavior data to the client; the server is used to send advertisement data matching the advertisement request to the client whenever receiving an advertisement request issued by the client; receive at least one user behavior data returned by the client within a preset time period to obtain a behavior data set; calculate the actual click-through rate of the target device in the preset time period based on the behavior data set; calculate the target sensitivity threshold using the actual click-through rate and the expected click-through rate, and replace the initial sensitivity threshold with the target sensitivity threshold to adjust the device interaction sensitivity of the server model.

[0012] According to another aspect of an embodiment of the present application, the present application provides an interactive sensitivity adjustment device, which is applied to a server, and the device includes: a first sending module, which is used to send advertising data matching the advertising request to the client whenever an advertising request is received from a client of a target device, so that the client displays the advertising content in the advertising data, wherein the advertising data includes the advertising content and the initial sensitivity threshold of the target device; a first receiving module, which is used to receive at least one user behavior data returned by the client within a preset time period to obtain a behavior data set, wherein the user behavior data is obtained by the client by monitoring whether the user triggers an interactive behavior on the target device, and whether the interactive behavior is triggered is determined based on the initial sensitivity threshold; a first calculation module, which is used to calculate the actual click-through rate of the target device in the preset time period according to the behavior data set; a second calculation module, which is used to calculate the target sensitivity threshold using the actual click-through rate and the expected click-through rate, and replace the initial sensitivity threshold with the target sensitivity threshold to adjust the device interaction sensitivity of the server model.

[0013] According to another aspect of an embodiment of the present application, the present application provides an interactive sensitivity adjustment device, which is applied to a client, and the device includes: a second sending module, used to send an advertising request to a server, wherein the advertising request carries the server model of a target device; a second receiving module, used to receive advertising data returned by the server, and display the advertising content in the advertising data; an extraction module, used to extract an initial sensitivity threshold from the advertising data, and use the initial sensitivity threshold to monitor the user's interactive behavior triggered by the advertising content to obtain user behavior data; a third sending module, used to send user behavior data to the client, so that the client calculates the target sensitivity threshold based on the user behavior data to adjust the interactive sensitivity of the target device.

[0014] According to another aspect of an embodiment of the present application, the present application provides an electronic device, including a memory, a processor, a communication interface and a communication bus, wherein the memory stores a computer program that can be run on the processor, the memory and the processor communicate through the communication bus and the communication interface, and the steps of the above method are implemented when the processor executes the computer program.

[0015] According to another aspect of an embodiment of the present application, the present application also provides a computer-readable medium having a non-volatile program code executable by a processor, and the program code enables the processor to execute the above method.

[0016] The above technical solution provided by the embodiment of the present application has the following advantages compared with the related art:

[0017] The present application is applied to the server through a method for adjusting interaction sensitivity, including: whenever an advertisement request is received from a client of a target device, advertisement data matching the advertisement request is sent to the client so that the client displays the advertisement content in the advertisement data, wherein the advertisement data includes the advertisement content and the initial sensitivity threshold of the target device; receiving at least one user behavior data returned by the client within a preset time period to obtain a behavior data set, wherein the user behavior data is obtained by the client by monitoring whether the user triggers interaction behavior on the target device, and whether the interaction behavior is triggered is determined based on the initial sensitivity threshold; calculating the actual click rate of the target device in the preset time period according to the behavior data set; calculating the target sensitivity threshold using the actual click rate and the expected click rate, and replacing the initial sensitivity threshold with the target sensitivity threshold to adjust the device interaction sensitivity of the server model. The actual click rate is calculated by collecting the user behavior data generated by the user under the initial sensitivity threshold, and then the initial sensitivity threshold of the device is adjusted according to the difference between the actual click rate and the expected click rate, thereby solving the problem that the interaction sensitivity of the device to the user cannot meet the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0020] Figure 1 A flowchart of an optional method for adjusting interaction sensitivity applied to a server according to an embodiment of the present application;

[0021] Figure 2 A flowchart of an optional method for adjusting interaction sensitivity applied to a client according to an embodiment of the present application;

[0022] Figure 3 A schematic diagram of an optional interaction sensitivity adjustment system provided according to an embodiment of the present application;

[0023] Figure 4 An interactive schematic diagram of an optional interactive sensitivity adjustment system provided according to an embodiment of the present application;

[0024] Figure 5 A block diagram of an optional device for adjusting interaction sensitivity applied to a server according to an embodiment of the present application;

[0025] Figure 6 A block diagram of an optional device for adjusting interaction sensitivity applied to a client according to an embodiment of the present application;

[0026] Figure 7 A schematic diagram of an optional electronic device structure provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0028] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present application and have no specific meaning. Therefore, "module" and "component" can be used interchangeably.

[0029] In Internet APPs, in addition to the common click and slide interaction methods, there are also some special interaction methods, such as "shake" and "twist", which are designed to provide a richer and more interesting user experience. These interesting interaction methods are achieved by collecting some sensor parameters of the device system (for example, acceleration, gravity sensing, etc.). When the user shakes the phone so that these sensing parameters meet certain threshold conditions, it is determined that the user triggers the interaction behavior, and then the APP performs corresponding interaction processing. The threshold condition here refers to the sensitivity parameter of shaking or twisting. The sensitivity parameter is generally tested repeatedly in the early stage, and the final value is finally determined based on the expected click rate and user experience.

[0030] However, for the same sensitivity threshold parameters, the sensitivity perceived by users on different device manufacturers or different models varies greatly. Some users feel that the shaking function is particularly insensitive, while some users feel that it is too sensitive. They may accidentally twist the device and trigger the jump of the interactive interface. This results in the device's interactive sensitivity to users not being able to meet the user experience.

[0031] In order to solve the problem mentioned in the background technology, according to one aspect of the embodiment of the present application, an embodiment of a method for adjusting interaction sensitivity is provided, which is applied to a server, such as Figure 1 As shown, including:

[0032] Step 101, whenever an advertisement request is received from a client of a target device, advertisement data matching the advertisement request is sent to the client, so that the client displays advertisement content in the advertisement data, wherein the advertisement data includes the advertisement content and an initial sensitivity threshold of the target device;

[0033] Step 103, receiving at least one user behavior data returned by the client within a preset time period, and obtaining a behavior data set, wherein the user behavior data is obtained by the client by monitoring whether the user triggers an interactive behavior on the target device, and whether the interactive behavior is triggered is determined based on an initial sensitivity threshold;

[0034] Step 105, calculating the actual click rate of the target device in a preset time period according to the behavior data set;

[0035] Step 107, using the actual click rate and the expected click rate to calculate the target sensitivity threshold, and using the target sensitivity threshold to replace the initial sensitivity threshold, so as to adjust the device interaction sensitivity of the server model.

[0036] The same sensitivity parameter (i.e., sensitivity threshold) will have different sensitivity experiences on different models because of the differences in the device system and hardware itself. The client, as application layer software, cannot change the differences in the device system and hardware. This requires solving this problem by optimizing the sensitivity threshold of the client's shaking interaction. Since different models have differences in their own systems and hardware, the purpose of optimization can be achieved by issuing different sensitivity thresholds based on such differences in different models. Therefore, this application calculates the sensitivity threshold that matches each server model, and issues the corresponding sensitivity threshold for different server models each time. This application is only illustrated by an embodiment of a method for adjusting the interaction sensitivity of a single server model.

[0037] Whenever the server receives an advertising request sent by the client, since the advertising request carries the server model, the server will find the initial sensitivity threshold corresponding to the server model in the cache, and recall the advertising content that matches the user preferences of the target device, and then return the initial sensitivity threshold and advertising content to the client. The client will then display the advertising content and respond to the user's interactive behavior according to the initial sensitivity threshold during the advertising content display period, while monitoring the user's interactive behavior.

[0038] At preset time intervals (e.g., every 24 hours), the server will receive the user behavior data sent by the client, but will only perform statistics within the preset time period (e.g., within 24 hours) to obtain a behavior data set, and then calculate the actual click rate of the target device within the preset time period based on the behavior data set, and then use the difference between the actual click rate and the expected click rate to adjust the initial sensitivity threshold.

[0039] For example, the server counts and analyzes data at a set frequency. If the frequency is set to 1 day, it means that the online click-through rate data of different models is counted every 1 day. When the advertising backend sends down the initial sensitivity threshold of the advertisement, it will perform corresponding weighting processing based on the click-through rate data of the latest model counted. After such offline data analysis and automatic optimization of the sent sensitivity threshold, the click-through rate of each model is finally maintained within a reasonable range of the standard, so that the shaking sensitivity perceived by each user is consistent.

[0040] Since the client determines the user's interactive behavior based on the initial sensitivity threshold, the accuracy of the initial sensitivity threshold is particularly important. After the server adjusts the initial sensitivity threshold to obtain the target sensitivity threshold each time, it will store the target sensitivity threshold and the server model in the cache. Then, when the ad request carrying the server model is received in the next cycle, the target sensitivity threshold corresponding to the server model will be read and sent to the client as the initial sensitivity threshold. In this way, the client can use the optimized and adjusted sensitivity threshold to respond to the user's shaking behavior, which can be closer to the user's interactive needs.

[0041] An optional embodiment calculates the actual click rate of a target device in a preset time period based on a behavior data set, including: counting a first number of user behavior data in the behavior data set, and using the first number as an exposure number; extracting a detection result from each user behavior data, wherein the detection result is used to indicate that the user has triggered a target operation or that the user has not triggered the target operation; counting the number of detection results indicating that the user has triggered the target operation to obtain a second number, and using the second number as the number of clicks; calculating a ratio of the number of clicks to the number of exposures, and determining the ratio as the actual click rate of the target device in the preset time period.

[0042] Specifically, under the same server model, receiving user behavior data once means that the advertising content is exposed once, so the number of user behavior data is the number of exposures.

[0043] After the advertisement is exposed, the user may not be interested, so the user's target operation may or may not be triggered. Therefore, it is necessary to determine whether the user has triggered the target operation or not based on the detection results, and then count the number of detection results indicating that the user has triggered the target operation to obtain a second number as the number of clicks. The number of clicks here represents the number of detection results indicating that the user has triggered the target operation rather than just the number of users clicking on the advertisement.

[0044] See below for details on user-triggered target actions.

[0045] By calculating the ratio of the number of clicks to the number of exposures, we can get the actual click rate of the target device in the preset time period.

[0046] After obtaining the actual click rate, it is necessary to further adjust the sensitivity threshold according to the difference between the actual click rate and the expected click rate, which is explained below.

[0047] An optional embodiment uses the actual click rate and the expected click rate to calculate the target sensitivity threshold, including: subtracting the expected click rate from the actual click rate to obtain the difference; if the difference is greater than 0, adding the initial sensitivity threshold to the preset step value to obtain the target sensitivity threshold; if the difference is less than 0, subtracting the preset step value from the initial sensitivity threshold to obtain the target sensitivity threshold; if the difference is equal to 0, using the initial sensitivity threshold as the target sensitivity threshold.

[0048] The expected click rate is the click rate that best matches the server model with the parameters to be adjusted, obtained through multiple experiments in advance.

[0049] If the actual click-through rate is greater than the expected click-through rate, it means that the initial sensitivity threshold is too small, so the initial sensitivity threshold needs to be increased. If the actual click-through rate is less than the expected click-through rate, it means that the initial sensitivity threshold is too large, so the initial sensitivity threshold needs to be reduced. If the actual click-through rate is equal to the expected click-through rate, it means that the initial sensitivity threshold is just right, so there is no need to adjust the initial sensitivity threshold, and the initial sensitivity threshold can be directly stored as the target sensitivity threshold.

[0050] The preset step value can be set according to actual conditions, and this application does not limit this.

[0051] For example, if the actual click rate of the model is x, and the expected click rate is y, then calculate the difference z between x and y. If the z value is greater than 0, it means that the actual click rate of the model is higher than the expected click rate, and the model is a more sensitive model. In this case, increase the initial sensitivity value w by a unit step size n, such as w+n, which is more difficult to shake than w. If the z value is less than 0, it means that the actual click rate of the model is lower than the expected click rate, and the model is less sensitive. In this case, reduce the sensitivity w by a unit step size n, such as wn, which is easier to trigger shaking than w. If the z value is equal to 0, it means that the sensitivity parameter of the current model has reached the target and no adjustment is required. The sensitivity parameter can continue to be sent as w. There are three possible sensitivities calculated in the end: wn, w, and w+n. The advertising engine on the server side sends the final calculated sensitivity parameter along with the advertising content. The client (front-end APP) uses the sensitivity parameter as a new sensitivity threshold to determine whether to trigger interaction when the user interacts. After the interaction is triggered, the reported click monitoring data must also carry w+n to the advertising backend for data storage processing.

[0052] The interactive sensitivity adjustment method provided in the present application can fully adaptively and dynamically optimize the sensitivity, and can be applied to the automatic optimization of the sensitivity thresholds of all models.

[0053] According to another aspect of the embodiment of the present application, the present application provides a method for adjusting interaction sensitivity, which is applied to a client, such as Figure 2 As shown, including:

[0054] Step 201, sending an advertisement request to a server, wherein the advertisement request carries the server model of the target device;

[0055] Step 203, receiving the advertisement data returned by the server, and displaying the advertisement content in the advertisement data;

[0056] Step 205, extracting an initial sensitivity threshold from the advertisement data, and using the initial sensitivity threshold to monitor the user's interactive behavior triggered by the advertisement content to obtain user behavior data;

[0057] Step 207: Send the user behavior data to the client, so that the client calculates the target sensitivity threshold according to the user behavior data to adjust the device interaction sensitivity.

[0058] After the client sends an advertising request with the server model of the target device to the server, it will receive the advertising content and the initial sensitivity threshold returned by the server. It then displays the advertising content while monitoring the user's interactive behavior based on the initial sensitivity threshold to obtain user behavior data. Finally, the user behavior data is sent to the server so that the server can calculate the target sensitivity threshold based on the user behavior data.

[0059] The interaction sensitivity adjustment method provided in this application can maintain the perception of all users in a relatively balanced state, so that users who do not want to shake the device but are prone to false triggering will no longer trigger it by mistake, avoiding the negative indicator problem of high click-through rate but low conversion rate, which can not only improve the overall promotion effect, but also improve the user experience.

[0060] As an optional embodiment, an initial sensitivity threshold is used to monitor the user's interactive behavior triggered by the advertising content to obtain user behavior data, including: detecting whether the user has triggered an interactive behavior in response to the advertising content, wherein the interactive behavior includes clicking behavior and shaking behavior; in the process of displaying the advertising content, if it is detected that the user has triggered an interactive behavior in response to the advertising content, then the user triggering the target operation is taken as the detection result; if it is not detected that the user has triggered an interactive behavior in response to the advertising content, then the user not triggering the target operation is taken as the detection result; and the detection result is used as user behavior data.

[0061] User-triggered target actions indicate that the user has clicked or shaken the current advertisement content.

[0062] Specifically, the click behavior can be determined whether to be triggered based on the touch recognition or button recognition on the device, and the shake behavior can be determined whether to be triggered based on the initial sensitivity threshold.

[0063] The user behavior data collected by the client includes the detection results, and then the user behavior data (carrying the server model) is sent to the server. The server calculates the number of exposures and clicks based on the user behavior data and the detection results.

[0064] According to another aspect of the embodiment of the present application, the present application provides an adjustment system for interaction sensitivity, such as Figure 3 As shown, the system includes a server 302 and a client 304, wherein:

[0065] The client 304 is used to send an advertisement request to the server, wherein the advertisement request carries the server model of the target device; receive advertisement data returned by the server, and display advertisement content in the advertisement data, wherein the advertisement data includes advertisement content and an initial sensitivity threshold of the target device; extract the initial sensitivity threshold from the advertisement data, and use the initial sensitivity threshold to monitor the user's interactive behavior triggered by the advertisement content to obtain user behavior data; and send the user behavior data to the client;

[0066] The server 302 is used to send advertising data matching the advertising request to the client whenever receiving an advertising request from the client; receive at least one user behavior data returned by the client within a preset time period to obtain a behavior data set; calculate the actual click rate of the target device within the preset time period based on the behavior data set; calculate the target sensitivity threshold using the actual click rate and the expected click rate, and replace the initial sensitivity threshold with the target sensitivity threshold to adjust the device interaction sensitivity of the server model.

[0067] The method embodiments applied to the client side and the method embodiments applied to the server side have been described above respectively and will not be repeated here.

[0068] Figure 4 An interactive schematic diagram of the interactive sensitivity adjustment system provided for the present application, as shown in the figure, the client APP represents the client in the present application, the advertising backend represents the server of the present application, the client APP sends a request carrying the device model to request an advertisement to the advertising backend, the advertising backend reads the sensitivity (here is the initial sensitivity threshold) and click-through rate (here is the expected click-through rate that matches the initial sensitivity threshold) stored in the cache, and then the advertising backend recalls the advertisement and returns the sensitivity and advertisement content to the client APP, the client APP displays the advertisement, responds to and monitors the user's shaking behavior when the advertisement is displayed, and reports the user's behavior data to the advertising backend, the advertising backend calculates the model click-through rate (i.e., the actual click-through rate) based on the user's behavior data, and then compares the actual click-through rate with the expected click-through rate, and adjusts the initial sensitivity threshold of the device of the current model according to the comparison result.

[0069] When the server sends an advertisement to the client, it also sends the initial sensitivity threshold applicable to the model. The client uses the initial sensitivity threshold obtained on the current device as the threshold to determine whether the user triggers the interaction. The sensitivity threshold sent by the server has an initial value, and needs to be optimized and adjusted according to the current user device model. When the shake click rate of the current model is too high, the sensitivity threshold is increased, and vice versa. The trigger sensitivity threshold is reduced. The server needs to analyze the click rate data of all online users by model to adjust the sensitivity threshold according to the model, and perform corresponding weighting processing based on the click rate statistics of each model to optimize the sensitivity threshold.

[0070] This application proposes a solution that can dynamically adjust the sensitivity thresholds of different models, which will allow users who have difficulty shaking to interact normally, and allow users who do not want to interact to avoid unnecessary false touches, especially avoid false jumps to advertisements, and balance the contradiction between click-through rate and user experience.

[0071] According to another aspect of the embodiment of the present application, the present application provides an adjustment device for interaction sensitivity, which is applied to a server, such as Figure 5 As shown, including:

[0072] A first sending module 502 is configured to send advertisement data matching the advertisement request to the client whenever an advertisement request is received from the client of the target device, so that the client displays advertisement content in the advertisement data, wherein the advertisement data includes the advertisement content and an initial sensitivity threshold of the target device;

[0073] A first receiving module 504 is used to receive at least one user behavior data returned by the client within a preset time period to obtain a behavior data set, wherein the user behavior data is obtained by the client monitoring whether the user triggers an interactive behavior on the target device, and whether the interactive behavior is triggered is determined based on an initial sensitivity threshold;

[0074] A first calculation module 506, configured to calculate an actual click rate of a target device in a preset time period according to the behavior data set;

[0075] The second calculation module 508 is used to calculate the target sensitivity threshold using the actual click rate and the expected click rate, and replace the initial sensitivity threshold with the target sensitivity threshold to adjust the device interaction sensitivity of the server model.

[0076] It should be noted that the first sending module 502 in this embodiment can be used to execute step 101 in the embodiment of the present application, the first receiving module 504 in this embodiment can be used to execute step 103 in the embodiment of the present application, the first computing module 506 in this embodiment can be used to execute step 105 in the embodiment of the present application, and the second computing module 508 in this embodiment can be used to execute step 107 in the embodiment of the present application.

[0077] Optionally, the first calculation module 506 is also used to count a first number of user behavior data in the behavior data set, and use the first number as the exposure number; extract detection results from each user behavior data, wherein the detection results are used to indicate that the user has triggered a target operation or that the user has not triggered the target operation; count the number of detection results indicating that the user has triggered the target operation to obtain a second number, and use the second number as the number of clicks; calculate the ratio of the number of clicks to the number of exposures, and determine the ratio as the actual click-through rate of the target device in a preset time period.

[0078] Optionally, the second calculation module 508 is also used to subtract the expected click-through rate from the actual click-through rate to obtain the difference; if the difference is greater than 0, the initial sensitivity threshold is added to the preset step value to obtain the target sensitivity threshold; if the difference is less than 0, the preset step value is subtracted from the initial sensitivity threshold to obtain the target sensitivity threshold; if the difference is equal to 0, the initial sensitivity threshold is used as the target sensitivity threshold.

[0079] According to another aspect of the embodiment of the present application, the present application provides an adjustment device for interaction sensitivity, which is applied to a client, such as Figure 6 As shown, the device comprises:

[0080] The second sending module 602 is used to send an advertisement request to the server, wherein the advertisement request carries the server model of the target device;

[0081] The second receiving module 604 is used to receive the advertisement data returned by the server and display the advertisement content in the advertisement data;

[0082] Extraction module 606, used to extract the initial sensitivity threshold from the advertisement data, and use the initial sensitivity threshold to monitor the user's interactive behavior triggered by the advertisement content to obtain user behavior data;

[0083] The third sending module 608 is used to send the user behavior data to the client, so that the client calculates the target sensitivity threshold according to the user behavior data to adjust the interaction sensitivity of the target device.

[0084] Optionally, the extraction module 606 is also used to detect whether the user has triggered an interactive behavior in response to the advertising content, where the interactive behavior includes clicking behavior and shaking behavior; in the process of displaying the advertising content, if it is detected that the user has triggered an interactive behavior in response to the advertising content, then the user triggering the target operation is taken as the detection result; if it is not detected that the user has triggered an interactive behavior in response to the advertising content, then the user not triggering the target operation is taken as the detection result; the detection result is used as user behavior data.

[0085] It should be noted that the second sending module 602 in this embodiment can be used to execute step 201 in the embodiment of the present application, the second receiving module 604 in this embodiment can be used to execute step 203 in the embodiment of the present application, the extraction module 606 in this embodiment can be used to execute step 205 in the embodiment of the present application, and the third sending module 608 in this embodiment can be used to execute step 207 in the embodiment of the present application.

[0086] It should be noted here that the examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the contents disclosed in the above embodiments.

[0087] According to another aspect of the embodiments of the present application, the present application provides an electronic device, such as Figure 7 As shown, it includes a memory 701, a processor 703, a communication interface 705 and a communication bus 707. The memory 701 stores a computer program that can be run on the processor 703. The memory 701 and the processor 703 communicate through the communication interface 705 and the communication bus 707. When the processor 703 executes the computer program, the steps of the above method are implemented.

[0088] The memory and processor in the above electronic device communicate via a communication bus and a communication interface. The communication bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus may be divided into an address bus, a data bus, a control bus, etc.

[0089] The memory may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0090] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0091] According to another aspect of the embodiments of the present application, a computer-readable medium having a non-volatile program code executable by a processor is provided.

[0092] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and this embodiment will not be described in detail here.

[0093] When the embodiments of the present application are specifically implemented, reference may be made to the above-mentioned embodiments, which have corresponding technical effects.

[0094] It is understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit may be implemented in one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), general purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in the present application, or a combination thereof.

[0095] For software implementation, the technology described herein can be implemented by a unit that performs the functions described herein. The software code can be stored in a memory and executed by a processor. The memory can be implemented in the processor or outside the processor.

[0096] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0097] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0098] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0099] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0100] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0101] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium, including several instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a ROM, a RAM, a magnetic disk or an optical disk. It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the term "include", "include" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements that are not explicitly listed, or also includes elements inherent to such a process, method, article or device. Without more constraints, an element defined by the phrase "comprising a..." does not exclude the existence of other identical elements in the process, method, article or apparatus comprising the element.

[0102] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest range consistent with the principles and novel features applied for herein.

Claims

1. A method for adjusting interaction sensitivity, characterized in that: Applied to the server, including: Whenever an advertisement request is received from a client of a target device, advertisement data matching the advertisement request is sent to the client so that the client displays advertisement content in the advertisement data, wherein the advertisement data includes the advertisement content and an initial sensitivity threshold of the target device; Receiving at least one user behavior data returned by the client within a preset time period to obtain a behavior data set, wherein the user behavior data is obtained by the client monitoring whether the user triggers an interactive behavior on the target device, and whether the interactive behavior is triggered is determined based on the initial sensitivity threshold; Calculating the actual click rate of the target device in the preset time period according to the behavior data set; The target sensitivity threshold is calculated using the actual click rate and the expected click rate, and the initial sensitivity threshold is replaced by the target sensitivity threshold to adjust the device interaction sensitivity of the server model.

2. The method according to claim 1, characterized in that Calculating the actual click rate of the target device in the preset time period according to the behavior data set includes: Counting a first quantity of the user behavior data in the behavior data set, and using the first quantity as an exposure quantity; Extracting a detection result from each of the user behavior data, wherein the detection result is used to indicate that the user triggers a target operation or that the user does not trigger the target operation; Counting the number of the detection results indicating that the user has triggered a target operation to obtain a second number, and using the second number as the number of clicks; The ratio of the number of clicks to the number of exposures is calculated, and the ratio is determined as the actual click rate of the target device in the preset time period.

3. The method according to claim 1, characterized in that The calculating the target sensitivity threshold by using the actual click rate and the expected click rate includes: Subtract the expected click rate from the actual click rate to obtain a difference; If the difference is greater than 0, the initial sensitivity threshold is added to the preset step value to obtain the target sensitivity threshold. If the difference is less than 0, the preset step value is subtracted from the initial sensitivity threshold to obtain the target sensitivity threshold. If the difference is equal to 0, the initial sensitivity threshold is used as the target sensitivity threshold.

4. A method for adjusting interaction sensitivity, characterized in that: Applied to the client, including: Sending an advertisement request to a server, wherein the advertisement request carries a server model of a target device; Receiving the advertisement data returned by the server, and displaying the advertisement content in the advertisement data; Extracting an initial sensitivity threshold from the advertisement data, and using the initial sensitivity threshold to monitor the user's interactive behavior triggered by the advertisement content to obtain user behavior data; The user behavior data is sent to the client, so that the client calculates a target sensitivity threshold according to the user behavior data to adjust the device interaction sensitivity.

5. The method according to claim 4, characterized in that The using the initial sensitivity threshold to monitor the user's interactive behavior triggered by the advertisement content to obtain user behavior data includes: Detecting whether the user triggers the interactive behavior in response to the advertisement content, wherein the interactive behavior includes a click behavior and a shake behavior; During the display of the advertisement content, if it is detected that the user triggers the interactive behavior with respect to the advertisement content, the user triggering the target operation is taken as the detection result; if it is not detected that the user triggers the interactive behavior with respect to the advertisement content, the user not triggering the target operation is taken as the detection result; The detection result is used as the user behavior data.

6. A system for adjusting interaction sensitivity, characterized in that: The system includes a server and a client, wherein: The client is used to send an advertisement request to a server, wherein the advertisement request carries a server model of a target device; receive advertisement data returned by the server, and display advertisement content in the advertisement data, wherein the advertisement data includes the advertisement content and an initial sensitivity threshold of the target device; extract the initial sensitivity threshold from the advertisement data, and use the initial sensitivity threshold to monitor the user's interactive behavior triggered by the advertisement content to obtain user behavior data; and send the user behavior data to the client; The server is used to send the advertisement data matching the advertisement request to the client whenever receiving the advertisement request sent by the client; receive at least one user behavior data returned by the client within a preset time period to obtain a behavior data set; calculate the actual click rate of the target device within the preset time period based on the behavior data set; calculate the target sensitivity threshold using the actual click rate and the expected click rate, and replace the initial sensitivity threshold with the target sensitivity threshold to adjust the device interaction sensitivity of the server model.

7. An adjustment device for interactive sensitivity, characterized in that: Applied to the server, the device comprises: A first sending module, configured to send advertisement data matching the advertisement request to the client whenever receiving an advertisement request from the client of the target device, so that the client displays advertisement content in the advertisement data, wherein the advertisement data includes the advertisement content and an initial sensitivity threshold of the target device; A first receiving module is configured to receive at least one user behavior data returned by the client within a preset time period to obtain a behavior data set, wherein the user behavior data is obtained by the client monitoring whether the user triggers an interactive behavior on the target device, and whether the interactive behavior is triggered is determined based on the initial sensitivity threshold; A first calculation module, configured to calculate an actual click rate of the target device in the preset time period according to the behavior data set; The second calculation module is used to calculate a target sensitivity threshold using the actual click rate and the expected click rate, and replace the initial sensitivity threshold with the target sensitivity threshold to adjust the device interaction sensitivity of the server model.

8. An adjustment device for interaction sensitivity, characterized in that: Applied to the client, including: A second sending module is used to send an advertisement request to the server, wherein the advertisement request carries a server model of a target device; A second receiving module, configured to receive the advertisement data returned by the server and display the advertisement content in the advertisement data; An extraction module, used to extract an initial sensitivity threshold from the advertisement data, and use the initial sensitivity threshold to monitor the user's interactive behavior triggered by the advertisement content to obtain user behavior data; The third sending module is used to send the user behavior data to the client, so that the client calculates a target sensitivity threshold according to the user behavior data to adjust the interaction sensitivity of the target device.

9. An electronic device, comprising a memory, a processor, a communication interface and a communication bus, wherein the memory stores a computer program that can be run on the processor, and the memory and the processor communicate through the communication bus and the communication interface, characterized in that: When the processor executes the computer program, the steps of the method described in any one of claims 1 to 3 or 4 to 5 are implemented.

10. A computer readable medium having a non-volatile program code executable by a processor, characterized in that: The program code enables the processor to execute the method of any one of claims 1 to 3 or 4 to 5.

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