Account recharge prompt method, device, electronic device and storage medium

Abstract

The embodiments of the present application disclose an account recharge reminder method, device, equipment and storage medium. The embodiments of the present invention can be applied to various scenarios, including cloud technology, artificial intelligence, smart transportation, assisted driving, etc. The account recharge reminder method includes: based on the historical expense consumption data corresponding to the account, predicting the expected expense consumption data corresponding to the account in the future time period; determining the supportable time length of the account balance according to the expected expense consumption data; if the supportable time length is less than the preset threshold, obtaining the average recharge cycle corresponding to the account, and determining the time length between the current time point and the target time point, the target time point is the most recent recharge time point from the current time point; if the time length between the current time point and the target time point is greater than the average recharge cycle, sending a recharge reminder message to the account. The embodiments of the present application can provide prompts in a timely manner when the account balance is insufficient, and can avoid excessive disturbance to the account.

Description

Technical Field

[0001] The present application relates to the technical field of information prompts, and in particular to an account recharge prompt method, device, electronic device, and storage medium. Background Art

[0002] With the continuous development of internet technology, applications have become increasingly widely used by users for internet activities. Typically, users can create at least one account within an application to complete business related to the corresponding application. For example, users can create a gaming account on a gaming platform to purchase gaming equipment, or create an advertising account on an advertising platform to place ads. Because account fees are consumed in real time, it is possible that the user of an account may have their balance depleted without being notified in a timely manner. Consequently, they may be unable to renew their fees in a timely manner, which in turn affects the effectiveness of the business processing associated with the account. Summary of the Invention

[0003] To solve the above technical problems, the embodiments of the present application provide an account recharge reminder method, an account recharge reminder device, an electronic device and a computer-readable storage medium, which can provide prompts in a timely manner when the account balance is insufficient and avoid excessive disturbance to the account.

[0004] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by practice of the present application.

[0005] According to one aspect of an embodiment of the present application, an account recharge reminder method is provided, including: based on the historical expense consumption data corresponding to the account, predicting the expected expense consumption data corresponding to the account in a future time period; determining the supportable time length of the account balance based on the expected expense consumption data; if the supportable time length is less than a preset threshold, obtaining the average recharge cycle corresponding to the account, and determining the time length between the current time point and the target time point, the target time point being the most recent recharge time point from the current time point; if the time length between the current time point and the target time point is greater than the average recharge cycle, sending a recharge reminder message to the account.

[0006] According to one aspect of an embodiment of the present application, an account recharge reminder device is provided, including: a prediction module, used to predict the expected expense consumption data corresponding to the account in a future time period based on the historical expense consumption data corresponding to the account; a determination module, used to determine the supportable time length of the account balance according to the expected expense consumption data; an acquisition module, used to obtain the average recharge cycle corresponding to the account when the supportable time length is less than a preset threshold, and determine the time length between the current time point and the target time point, the target time point being the most recent recharge time point from the current time point; a sending module, used to send a recharge reminder message to the account when the time length between the current time point and the target time point is greater than the average recharge cycle.

[0007] According to one aspect of an embodiment of the present application, an electronic device is provided, including a processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the above-mentioned account recharge prompt method is implemented.

[0008] According to one aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor of a computer, the computer executes the account recharge prompt method provided above.

[0009] According to one aspect of an embodiment of the present application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the account recharge prompt method provided in the various optional embodiments described above.

[0010] In the technical solution provided in the embodiments of the present application, the supportable time length of the account balance is determined based on the expected expense consumption data corresponding to the account in the future time period. When the supportable time length is less than a preset threshold, the average recharge cycle corresponding to the account is obtained, and the time length between the current time point and the target time point is determined. If the time length between the current time point and the target time point is greater than the average recharge cycle, a recharge reminder message is sent to the account. The above-mentioned account recharge reminder method combines the account balance and the user's average recharge cycle to remind the account to recharge. It can not only remind the account to recharge in time when the account balance is insufficient, but also avoid unnecessary disturbances caused by premature recharge reminders to the account, thereby improving user experience.

[0011] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The accompanying drawings are incorporated into and constitute a part of the specification, illustrating embodiments consistent with the present application and, together with the specification, serving to explain the principles of the present application. It is obvious that the drawings described below are merely some embodiments of the present application, and a person of ordinary skill in the art can derive other drawings based on these drawings without inventive effort. In the drawings:

[0013] Figure 1 is a flowchart of an account recharge reminder method shown in an exemplary embodiment of the present application;

[0014] Figure 2 This is a flow chart of an account receiving a recharge reminder message according to an exemplary embodiment of the present application;

[0015] Figure 3 This is a flowchart of an advertising account recharge prompt method shown in an exemplary embodiment of the present application;

[0016] Figure 4 yes Figure 1 Step S100 in the illustrated embodiment is a flow chart of an exemplary embodiment;

[0017] Figure 5 yes Figure 4 Step S110 in the illustrated embodiment is a flow chart of an exemplary embodiment;

[0018] Figure 6 This is a flowchart of an exemplary embodiment provided by the present application showing how to use the ARIMA model to predict expected cost consumption data in a future time period;

[0019] Figure 7 yes Figure 1 Step S200 in the illustrated embodiment is a flow chart of an exemplary embodiment;

[0020] Figure 8 yes Figure 1 Step S400 in the illustrated embodiment is a flow chart of an exemplary embodiment;

[0021] Figure 9 yes Figure 8 Step S410 in the illustrated embodiment is a flow chart of an exemplary embodiment;

[0022] Figure 10 is a block diagram of an account recharge reminder device shown in an exemplary embodiment of the present application;

[0023] Figure 11 A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0024] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. When the following description refers to the drawings, identical numerals in different figures represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0025] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0026] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0027] It should also be noted that the term "plurality" used in this application refers to two or more. "And / or" describes the relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, or B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0028] Existing technologies typically only prompt users to top up their accounts when their assets are depleted and they can no longer perform related services. This approach degrades the user experience. The few existing top-up prompts use historical asset consumption data to predict future asset consumption data, then issue top-up prompts based on the account balance and predicted asset consumption data. This prompt method provides a recharge reminder at any time as long as the balance does not meet the preset conditions, which can cause unnecessary interruptions to users.

[0029] To address at least the aforementioned issues in the prior art, the present invention provides an account recharge reminder method, an account recharge reminder device, an electronic device, and a computer-readable storage medium. These embodiments are described in detail below. The present invention can be applied to various scenarios, including but not limited to cloud technology, artificial intelligence, smart transportation, and assisted driving.

[0030] See also Figure 1 , Figure 1FIG. 1 is a flow chart of an account recharge reminder method shown in an exemplary embodiment of the present application. Figure 1 As shown, the account recharge prompt method provided in this embodiment includes steps S100 to S400, and the detailed description is as follows:

[0031] Step S100: Based on the historical expense consumption data corresponding to the account, predict the expected expense consumption data corresponding to the account in a future time period.

[0032] The account of this embodiment supports virtual accounts of various application scenarios, such as game accounts, advertising accounts, financial accounts, etc., which are not specifically limited here. The account includes an account name, an IP address of the account, or a mobile phone number bound to the account.

[0033] In this embodiment, the historical expense consumption data corresponding to an account can be counted in different time units according to different specific application scenarios, for example, the historical expense consumption data corresponding to an account can be counted daily, or weekly. Alternatively, if the account's expenses are consumed quickly, the historical expense consumption data corresponding to an account can be counted hourly, etc., without specific limitation here.

[0034] It's easy to understand that historical expense data that's too far removed from the current time point may be of little value in predicting projected expense data for future time periods. Including this data in the forecast will not only increase the computational workload and waste computing resources, but may also reduce the accuracy of the forecast. For example, a historical time period is pre-set, such as one month prior to the current time point, so that historical expense data for the month prior to the current time point can be obtained to predict the corresponding projected expense data for the account in the future time period.

[0035] For example, if the account is new, that is, it has no corresponding historical expense data, then the user is checked to see if they have other accounts of the same type. If so, the historical expense data corresponding to those accounts is obtained as the historical expense data corresponding to the new account. If not, the historical expense data corresponding to other accounts of the same type is obtained as the historical expense data corresponding to the new account. Here, other accounts of the same type refer to other accounts with similar expense habits as the new account.

[0036] Exemplarily, the historical cost consumption data corresponding to each advertising account is collected through the database of the advertising platform, for example, a video platform. It should be noted that if an advertising account is used to spend money on multiple advertisements on the same video platform, the historical cost consumption data corresponding to the advertising account is the total historical cost consumption data of multiple advertisements.

[0037] Exemplarily, the average historical cost consumption data of the historical cost consumption data is calculated, and the historical cost consumption data is used as the corresponding estimated cost consumption data in the future time period. Of course, this embodiment can also predict the corresponding estimated cost consumption data in the future time period in other ways, for example, by constructing a machine learning model, and predicting the corresponding estimated cost consumption data in the future time period based on the historical cost consumption data. Machine learning is a multi-disciplinary cross-disciplinary subject involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and other disciplines. It specializes in studying how computers simulate or implement human learning behavior to acquire new knowledge or skills, and reorganize existing knowledge structures to continuously improve their own performance. Machine learning is the core of artificial intelligence and the fundamental way to make computers intelligent. Its applications are spread across all areas of artificial intelligence. Machine learning and deep learning generally include artificial neural networks, belief networks, reinforcement learning, transfer learning, inductive learning, and teaching learning.

[0038] Step S200: Determine the supportable time length of the account balance based on the estimated expense consumption data.

[0039] In this embodiment, starting from the current time point, the account balance will be consumed within the time period of the supportable time length.

[0040] In this embodiment, the supportable time length can be calculated based on the corresponding estimated cost consumption data and account balance in the future time period. For example, if the estimated cost consumption data for the next five days, in descending order from the current time point, are 3, 4, 2, 7, and 6 respectively, and the account balance is 7, then the supportable time length of the account can be determined to be 2 days.

[0041] Step S300: If the supported time length is less than the preset threshold, obtain the average recharge cycle corresponding to the account, and determine the time length between the current time point and the target time point, where the target time point is the recharge time point closest to the current time point.

[0042] In this embodiment, if the supported time length is greater than the preset threshold, it means that the account balance is still sufficient and there is no need to remind the account to recharge. Otherwise, it is necessary to further determine whether to remind the account to recharge based on the average recharge cycle corresponding to the account to avoid unnecessary disturbance to the user by reminding the account to recharge too early.

[0043] For example, if the account is new, that is, it has no corresponding average recharge cycle, the system checks whether the user has used other accounts of the same type. If so, the average recharge cycle corresponding to the same account is obtained as the average recharge cycle corresponding to the new account. If not, the average recharge cycle corresponding to other accounts of the same type is obtained as the average recharge cycle corresponding to the new account. Here, other accounts of the same type refer to other accounts with similar spending habits as the new account.

[0044] Step S400: If the time length between the current time point and the target time point is greater than the average recharge cycle, a recharge reminder message is sent to the account.

[0045] This embodiment only sends a recharge reminder message to the account when the time between the current time point and the target time point exceeds the average recharge cycle, thereby avoiding unnecessary interruptions to the user caused by premature recharge reminders. For example, if the user's recharge cycle is stable at 10 days, and the balance reaches the preset threshold in the above method two days before the user's next recharge, the recharge reminder will be triggered. In reality, the user is likely to recharge after two days, so it will cause interruptions.

[0046] For example, see Figure 2 , Figure 2 FIG. 1 is a flow chart of an exemplary embodiment of the present application showing an account receiving a recharge reminder message. Figure 2 As shown, the account receiving the recharge reminder message includes steps S21-S23:

[0047] S21: Select to enable the recharge reminder function.

[0048] For example, an account whose account fee consumption reaches a certain level can choose whether to enable the insufficient balance reminder function. If the insufficient balance reminder function is enabled, the system periodically calculates whether the account needs a recharge reminder through the account recharge reminder method provided in this embodiment, and sends a recharge reminder message.

[0049] S22: Select a method for sending the recharge reminder message.

[0050] For example, an account can choose to have the reminder message sent to the account consumption interface, the user's bound mobile phone number, or the terminal device where WeChat is located. For example, an advertising account can choose to have the reminder message displayed on the advertising delivery platform, such as the message interface of the iQiyi video platform.

[0051] Exemplarily, the method of sending the recharge reminder message to the account is determined based on the account information that can be obtained. For example, if the IP address of the account is obtained, the recharge reminder message is sent to the account via the network. If the phone number of the account is obtained or the user terminal where the account is located is not connected to the Internet, the recharge reminder message is sent to the account by sending a text message or making a phone call.

[0052] S23: Receive a recharge reminder message.

[0053] The above-mentioned account recharge reminder method enables users to determine whether to turn on the account recharge reminder function and determine the account recharge reminder method by themselves, which is more humane and improves the user experience.

[0054] For example, to avoid excessively disturbing users, the number of recharge reminder messages sent can be personalized, for example, limiting them to a preset number of times per day, such as once or twice. For example, if the time between the current time point and the target time point is greater than the average recharge cycle, a determination is made as to whether the account has received m recharge reminders within n days, where n is the number of cool-down days. If so, no recharge reminder message is sent to the account. For example, a determination is made as to whether the account has received two recharge reminders within 15 days.

[0055] The account recharge reminder method provided in this embodiment determines the supportable time length of the account balance based on the expected expense consumption data corresponding to the account in a future time period. When the supportable time length is less than a preset threshold, the average recharge cycle corresponding to the account is obtained, and the time length between the current time point and the target time point is determined. If the time length between the current time point and the target time point is greater than the average recharge cycle, a recharge reminder message is sent to the account. The above-mentioned account recharge reminder method combines the account balance and the user's average recharge cycle to remind the account to recharge. It can not only timely remind the account to recharge when the account balance is insufficient, but also avoid unnecessary disturbances caused by premature account recharge reminders, thereby improving user experience.

[0056] In one example application scenario, with the continuous development of internet technology, applications have become increasingly popular among users for online activities. Therefore, displaying advertisements within applications has become a primary method for promoting businesses or information. When ads are displayed within applications, advertisers are required to pay corresponding advertising fees.

[0057] Since the advertising fees paid by advertisers are consumed in real time in the advertising delivery system, it is possible that the advertising fees paid by an advertiser have been consumed, but the advertiser is not informed of this fact in a timely manner and is unable to re-pay the advertising fees in time, thus affecting the effectiveness of the advertising delivery.

[0058] For example, if the time length between the current time point and the target time point is less than or equal to the average recharge cycle, and the day after the current time point is a holiday, a recharge reminder message is sent to the account.

[0059] After long-term research, the inventors of this application have found that the possibility of users logging into the system and performing recharge operations during statutory holidays is significantly reduced compared to non-holidays. Therefore, this embodiment sends a recharge reminder message to the account when the time length between the current time point and the target time point is less than or equal to the average recharge cycle, and the day after the current time point is a holiday. This recharge reminder method not only reduces disturbance to the user but is also more humane. For example, if the third day after the current time point is a holiday, the expected cost consumption data for the first day of the future is predicted to be 3 units, the expected cost consumption data for the second day of the future is predicted to be 5 units, and the expected cost consumption data for the first day of the future is predicted to be 13 units, and the current balance is 8 units. Therefore, the supported time length is 2 days, excluding the holiday. In this case, a recharge reminder message needs to be sent to the account.

[0060] For example, see Figure 3 , Figure 3 This is a flowchart of an advertising account recharge prompt method shown in an exemplary embodiment of the present application. An advertising account is an account built in an advertising platform for placing advertisements, such as a video platform, a public account platform, etc. Figure 3 As shown, the advertising account recharge prompt method provided in this embodiment includes steps S11-S17:

[0061] Step S11: Based on the historical advertising expense consumption data corresponding to the advertising account, predict the expected advertising expense consumption data corresponding to the advertising account in a future time period.

[0062] Step 12: Determine the duration of the advertising account balance based on the estimated advertising expenditure data;

[0063] Step S13: Determine whether the supportable time length is less than a preset threshold;

[0064] Step S14: Obtain the average recharge cycle corresponding to the advertising account, and determine the time length between the current time point and the target time point, where the target time point is the most recent recharge time point from the current time point;

[0065] Step S15: Determine whether the time length is greater than the average recharge cycle.

[0066] Step S16: If the time length is greater than the average recharge cycle and the supportable time length is less than the preset threshold, determine whether reminder information has been sent M times within N days, where N and M are positive integers greater than zero.

[0067] Step S17: Send a recharge reminder message to the advertising account.

[0068] It should be noted that, in this embodiment, there is no limitation on the execution order of steps S11-S13 and steps S14-S15. For example, steps S11-S13 or steps S14-S15 may be executed first, or steps S11-S13 and steps S14-S15 may be executed simultaneously.

[0069] By providing an account recharge reminder for the advertising account in the above manner, it is possible to timely provide an advertising account recharge reminder when the advertising account balance is insufficient, and to avoid unnecessary interruptions caused by premature advertising account recharge reminders, thereby improving user experience.

[0070] For example, see Figure 4 , Figure 4 yes Figure 1 Step S100 in the embodiment shown is a flow chart of an exemplary embodiment, as shown in FIG. Figure 4 As shown, step S100 includes steps S110 to S120, which are described in detail as follows:

[0071] Step S110: converting the historical expense consumption data into a historical expense consumption time series.

[0072] A time series (or dynamic series) is a sequence of values ​​of the same statistical indicator arranged in chronological order. The main purpose of time series analysis is to predict the future based on existing historical data. Depending on the observation period, the time in a time series can be years, quarters, months, or any other time format.

[0073] In this embodiment, the historical expense consumption time series refers to a series of historical expense consumption data arranged in chronological order of occurrence, so as to facilitate subsequent time series analysis of the historical expense consumption data and further predict the expected expense consumption time series corresponding to the account in the future time period.

[0074] For example, see Figure 5 , Figure 5 yes Figure 4 Step S110 in the embodiment shown is a flow chart of an exemplary embodiment, as shown in FIG. Figure 5 As shown, step S110 includes steps S111 to S113, which are described in detail as follows:

[0075] Step S111: If the preset historical time period includes the first holiday, the target historical expense consumption data is used as the historical expense consumption data corresponding to the first holiday.

[0076] This embodiment takes into account that although the expense consumption data of an account has a certain periodicity, a time series analysis algorithm model can be used to predict the corresponding expected expense consumption data in a future time period. However, since the expense consumption data of an account is usually larger than that of non-holidays, the annual holidays will greatly affect the expense consumption data of the account. In addition, the dates of the Gregorian calendar holidays are fixed each year, while the dates of the lunar calendar holidays are not fixed each year. This characteristic of holidays can easily cause inaccuracies in the prediction.

[0077] To eliminate the potential inaccuracies that holidays may introduce into model predictions, this embodiment uses the target historical expense data as the historical expense data corresponding to the first holiday, thereby improving the accuracy of the predicted expense data for the account in the future time period. The target historical expense data is the average historical expense data corresponding to a preset length of time near the holiday within a preset historical time period. In this embodiment, the holiday can be any national statutory holiday, such as Mid-Autumn Festival, Dragon Boat Festival, May Day, Saturdays and Sundays, etc.

[0078] For example, the account recharge notification method provided in this embodiment is applied to an advertising platform. After obtaining historical expense data for an advertisement related to rice dumplings, it is identified that the expense data for the advertising account on the Dragon Boat Festival is significantly higher than the expense data for other dates. Therefore, this embodiment uses the average expense data for N days before and after the Dragon Boat Festival as the historical expense data for the Dragon Boat Festival. N can be set based on the actual application scenario and is not specifically limited here.

[0079] Step S112: Counting historical expense consumption data corresponding to other dates except the first holiday within a preset historical time period.

[0080] In this embodiment, the historical expense consumption data of non-holiday periods within a preset historical time period may be obtained using days as a time unit.

[0081] Step S113: Arrange the historical expense consumption data of each day within a preset historical time period in chronological order to obtain a historical expense consumption time series.

[0082] This embodiment obtains the historical expense consumption time series corresponding to the account in the above manner, which can eliminate the inaccuracy that holidays may cause to the model prediction.

[0083] Step S120: inputting the historical expense consumption time series into the account expense consumption prediction model to obtain the estimated expense consumption data corresponding to the account output by the account expense consumption prediction model in the future time period.

[0084] In this embodiment, the account expense consumption forecasting model is a time series forecasting model. A time series forecasting model is a theory and method for establishing a mathematical model through curve fitting and parameter estimation based on time series data obtained from system observations. Curve fitting and parameter estimation methods (such as nonlinear least squares) are generally used for forecasting. Time series forecasting models include simple averaging algorithm models, sliding window averaging algorithm models, simple exponential smoothing algorithm models, ARMA models (autoregressive moving average models), ARIMA models (autoregressive integrated moving average models), and the like.

[0085] To improve forecast accuracy, this embodiment prefers to use the ARIMA model to forecast the expected expense data for future time periods. The ARIMA model is a model that converts a non-stationary time series into a stationary time series and then regresses the dependent variable only on its lagged value and the present and lagged values ​​of the random error term. In ARIMA(p, d, q), p is the number of autoregressive terms, q is the number of moving average terms, and d is the number of differencing operations performed to transform the historical expense time series into a stationary time series.

[0086] ARIMA (p, d, q) model Specifically, the ARIMA model can be expressed as follows:

[0087]

[0088] Among them, X t is the expected cost consumption data corresponding to the future time period, ε t is the error, and θ i is a parameter and L is the lag operator.

[0089] For example, see Figure 6 , Figure 6 This is a flowchart of an exemplary embodiment provided by the present application showing how to use the ARIMA model to predict the expected cost consumption data in the future time period. Figure 6 As shown, the ARIMA model predicts the expected cost consumption data in the future time period, including steps S50-S70:

[0090] Step S50: Convert the historical cost consumption time series into a stationary time series.

[0091] In this step, the historical expense consumption time series is plotted to see whether it is a stationary time series. For non-stationary time series, a d-order difference operation must be performed first to transform it into a stationary time series. For example, advertising data generally requires a 1st-order difference.

[0092] Step S60: Determine parameters p and q.

[0093] In this step, the autocorrelation coefficient ACF and the partial autocorrelation coefficient PACF of the above-mentioned stationary time series are obtained, and the optimal layer p and order q are obtained by analyzing the autocorrelation graph and the partial autocorrelation graph.

[0094] Step S70: Perform data fitting on the ARIMA (p, d, q) model to obtain the corresponding estimated expense consumption data of the account in the future time period.

[0095] It should be noted that the ARIMA algorithm model is not the only prediction model or algorithm. Other algorithms or models can also be used to predict the corresponding expected cost consumption data in the future time period. It is just that this model is the most accurate prediction model and is also the preferred model in this embodiment.

[0096] For example, see Figure 7 , Figure 7 yes Figure 1 Step S200 in the embodiment shown is a flow chart of an exemplary embodiment, as shown in FIG. Figure 7 As shown, step S200 includes steps S210 to S220, which are described in detail as follows:

[0097] Step S210: If the future time period includes the second holiday, the final estimated cost consumption data for the holiday is determined based on the estimated cost consumption data corresponding to the second holiday and the cost consumption growth rate corresponding to the second holiday.

[0098] In order to improve the prediction accuracy of the account expense consumption prediction model, this embodiment uses the target historical expense consumption data as the historical expense consumption data corresponding to the holidays in step S111, which makes the estimated expense consumption data corresponding to the holidays output by the account expense consumption prediction model inaccurate. Therefore, in this step, in order to compensate for the above inaccuracy, the final estimated expense consumption data for the second holiday is determined based on the estimated expense consumption data corresponding to the second holiday and the expense consumption growth rate corresponding to the second holiday, so as to further improve the accuracy of judging whether to prompt the account to recharge.

[0099] Specifically, let the cost consumption growth rate corresponding to the second holiday be τ, and the estimated cost consumption data corresponding to the second holiday be k1. Then the calculation formula for the final estimated cost consumption data K1 of the second holiday is:

[0100] K1=k1*(τ+1)

[0101] In this embodiment, the cost consumption growth rate corresponding to the second holiday is determined based on the historical cost consumption data corresponding to the first holiday and the target historical cost consumption data, and the target historical cost consumption data is the average historical cost consumption data corresponding to the preset time length close to the first holiday within the preset historical time period.

[0102] Specifically, let's assume that the historical cost consumption data corresponding to the first holiday is K2, and the target historical cost consumption data is k2. Then the calculation formula for the cost consumption growth rate τ corresponding to the second holiday is:

[0103] τ=(K2-k2) / k2

[0104] Step S220: Determine the supportable time length based on the final estimated cost consumption data corresponding to the second holiday, the estimated cost consumption data corresponding to other dates, and the account balance.

[0105] In this embodiment, according to the second holiday and other dates in the future time period, the final estimated cost consumption data corresponding to the two holidays and the estimated cost consumption data corresponding to other dates in the future time period are directly added up in order from near to far from the date of the current time point. The date at which the current balance is exhausted is taken as the end point of the supportable time length, and the supportable time length can be determined in combination with the date of the current time point.

[0106] This embodiment determines the final estimated expense consumption data for holidays based on the estimated expense consumption data corresponding to holidays and the expense consumption growth rate corresponding to holidays output by the account expense consumption prediction model, and then determines the supportable time length based on the final estimated expense consumption data corresponding to holidays, the estimated expense consumption data corresponding to other dates and the account balance, thereby ensuring the accuracy of the recharge reminder time.

[0107] For example, see Figure 8 , Figure 8 yes Figure 1 Step S400 in the embodiment shown is a flow chart of an exemplary embodiment, as shown in FIG. Figure 8 As shown, step S400 includes steps S410 to S420, which are described in detail as follows:

[0108] Step S410: Obtain the total amount of estimated cost consumption corresponding to the next N days.

[0109] In this embodiment, first, based on the historical expense consumption data corresponding to the account, the total expected expense consumption data corresponding to each day in the next N days is predicted, and then the total expected expense consumption data corresponding to each day in the next N days is added up to obtain the total expected expense consumption amount corresponding to the next N days.

[0110] In this embodiment, N is a value corresponding to the average recharge cycle.

[0111] For example, see Figure 9 , Figure 9 yes Figure 8 Step S410 in the embodiment shown is a flow chart of an exemplary embodiment, as shown in FIG. Figure 9 As shown, step S410 includes steps S411 to S412, which are described in detail as follows:

[0112] Step S411: Calculate the sum of the average fee recharge amount and the average fee bid corresponding to the accounts in the same industry on a month-on-month basis to obtain the month-on-month sum value.

[0113] In this embodiment, the same industry accounts are one or more accounts with the same performance ranking as the corresponding account.

[0114] The month-on-month (MM / YoY) ratio indicates the change in a quantity over two consecutive statistical periods (e.g., two consecutive months). The month-on-month growth rate is the ratio of the level in the reporting period to the level in the previous period, indicating the rate of development of the phenomenon from period to period. For example, comparing each month within a year with the previous month—February versus January, March versus February, April versus March, and so on, December versus November—describes the degree of development from month to month.

[0115] The month-on-month change in the recharge amount represents the ratio of change in the recharge amount over two consecutive recharge periods. In this embodiment, the month-on-month change in the recharge amount for each recharge period for accounts in the same industry is calculated, and then the average of the multiple month-on-month changes in the recharge amount is calculated to obtain the average month-on-month change in the recharge amount.

[0116] The average bid price represents the change in bid amounts over two consecutive bid cycles. For example, an advertising account bids on an advertising platform for its pending ads, so that the platform deducts fees based on the bid price when the corresponding ad is delivered. Generally, the higher the bid price, the higher the priority for delivery. In this example, the average bid price is calculated for each bid cycle for accounts in the same industry. The average bid price is then averaged to obtain the average bid price.

[0117] Step S412: Determine the total amount of estimated cost consumption based on the estimated cost consumption data corresponding to each day in the next N days and the month-on-month sum.

[0118] In this embodiment, when the sum of the average fee recharge amount and the average fee bid corresponding to accounts in the same industry is large on a month-on-month basis, it is believed that the industry will most likely usher in a marketing node in the future, and the competitiveness of other accounts in the same industry will be enhanced. The account needs to increase recharge and raise the bid, otherwise it will affect the business competitiveness and thus the business processing effect. Therefore, this embodiment determines the total amount of expected fee consumption based on the expected fee consumption data corresponding to each day in the next N days and the month-on-month sum, so that the recommended recharge amount subsequently determined based on the total amount of expected fee consumption has more advantages in the entire industry.

[0119] In this embodiment, the total estimated cost consumption amount c is determined according to the following formula:

[0120]

[0121] Among them, precost i is the expected cost consumption data corresponding to the future i-th day, θ is the average cost recharge amount corresponding to accounts in the same industry on a month-on-month basis, and ∈ is the average cost bid corresponding to accounts in the same industry on a month-on-month basis.

[0122] Since the possibility of users logging into the system and performing recharge operations during statutory holidays is greatly reduced compared to non-holidays, for example, if M days after the next N days are holidays, the total estimated cost consumption amount is determined based on the estimated cost consumption data corresponding to each day in the next N+M days and the month-on-month sum, where N is the average recharge cycle.

[0123] In this embodiment, the total estimated cost consumption amount c is determined according to the following formula:

[0124]

[0125] Through the above method, the recommended recharge amount determined based on the estimated total amount of expense consumption can be maintained until the end of the holiday, reducing the possibility of users recharging their accounts during holidays and improving user experience.

[0126] Step S420: Generate a recharge reminder message based on the recommended recharge amount, the estimated support time, the account balance, and the support time, and send the recharge reminder message to the account.

[0127] In this embodiment, the recommended top-up amount is the estimated total cost, and the estimated support time is the value corresponding to the average top-up period. The estimated support time can also be the value corresponding to (N+M), where N is the average top-up period and M is the value corresponding to the number of statutory holidays after the average top-up period.

[0128] Exemplarily, the message format of the recharge reminder message generated by this embodiment is: "Insufficient balance reminder: the current account balance is a yuan, and the estimated support time length is b days; it is recommended to recharge c yuan (the average fee recharge amount corresponding to accounts in the same industry has increased significantly on a month-on-month basis and the average fee bid has increased significantly on a month-on-month basis. It is recommended to increase the recharge amount and raise the bid to improve competitiveness / it is expected to usher in a marketing node for this industry / it will be a statutory holiday in xx days, so it is recommended to increase the recharge amount). After recharging, it is estimated that it can support delivery for d days." If the information in brackets exists after calculation by the system, it will be sent, otherwise it will not be sent. Among them, a is the current balance value, b is the value corresponding to the support time length, c is the recommended recharge amount, and d is the average recharge cycle.

[0129] The above-mentioned method of prompting accounts to recharge can give the corresponding recommended recharge amount for the account based on factors such as the behavior of accounts in the same industry and holidays, which facilitates users to make recharge decisions and guides users to achieve better delivery results.

[0130] participate Figure 10 , Figure 10 FIG. 1 is a block diagram of an account recharge reminder device shown in an exemplary embodiment of the present application. Figure 10 As shown, the application page display device 80 includes a prediction module 81 , a determination module 82 , an acquisition module 83 and a sending module 84 .

[0131] Among them, the prediction module 81 is used to predict the expected expense consumption data corresponding to the account in the future time period based on the historical expense consumption data corresponding to the account; the determination module 82 is used to determine the supportable time length of the account balance based on the expected expense consumption data; the acquisition module 83 is used to obtain the average recharge cycle corresponding to the account when the supportable time length is less than the preset threshold, and determine the time length between the current time point and the target time point, the target time point being the most recent recharge time point from the current time point; the sending module 84 is used to send a recharge reminder message to the account when the time length between the current time point and the target time point is greater than the average recharge cycle.

[0132] In another exemplary embodiment, the prediction module 81 includes a conversion unit and a prediction unit, wherein the conversion unit is used to convert historical expense consumption data into a historical expense consumption time series; the prediction unit is used to input the historical expense consumption time series into the account expense consumption prediction model to obtain the estimated expense consumption data corresponding to the account output by the account expense consumption prediction model in the future time period.

[0133] In another exemplary embodiment, the conversion unit includes a first conversion sub-unit, a second conversion sub-unit, and an arrangement sub-unit. The first conversion sub-unit is configured to, when a preset historical time period includes a first holiday, use the target historical expense consumption data as the historical expense consumption data corresponding to the first holiday. The target historical expense consumption data is the average historical expense consumption data corresponding to a preset length of time adjacent to the first holiday within the preset historical time period. The second conversion sub-unit is configured to collect historical expense consumption data corresponding to dates other than the first holiday within the preset historical time period. The arrangement sub-unit is configured to arrange the historical expense consumption data for each day within the preset historical time period in chronological order to obtain a historical expense consumption time series.

[0134] In another exemplary embodiment, determination module 82 includes a first determination unit and a second determination unit. The first determination unit is configured to determine, when the future time period includes a second holiday, final estimated expense consumption data for the second holiday based on the estimated expense consumption data corresponding to the second holiday and the expense consumption growth rate corresponding to the second holiday, the expense consumption growth rate corresponding to the second holiday being determined based on historical expense consumption data corresponding to the first holiday and target historical expense consumption data. The second determination unit is configured to determine the supportable time length based on the final estimated expense consumption data corresponding to the second holiday, estimated expense consumption data corresponding to other dates, and the account balance.

[0135] In another exemplary embodiment, the sending module 84 is further configured to send a recharge reminder message to the account when the time length between the current time point and the target time point is less than or equal to the average recharge cycle and the day after the current time point is a holiday.

[0136] In another exemplary embodiment, the sending module 84 includes an acquisition unit and a sending unit, wherein the acquisition unit is used to obtain the total amount of estimated cost consumption corresponding to the next N days, where N is the value corresponding to the average recharge cycle; the sending unit is used to generate a recharge reminder message based on the recommended recharge amount, the estimated supportable time length, the account balance, and the supportable time length, and send the recharge reminder message to the account, wherein the recommended recharge amount is the estimated total amount of cost consumption, and the estimated supportable time length is the value corresponding to the average recharge cycle.

[0137] In another exemplary embodiment, the acquisition unit includes a calculation subunit and an acquisition subunit, wherein the calculation subunit is used to calculate the sum of the average fee recharge amount and the average fee bid corresponding to accounts in the same industry on a month-on-month basis to obtain the month-on-month sum value, and accounts in the same industry are accounts with top performance rankings in the same industry as the account corresponding to; the acquisition subunit is used to determine the total amount of expected fee consumption based on the expected fee consumption data corresponding to each day in the next N days and the month-on-month sum value.

[0138] It should be noted that the apparatus provided in the above embodiment and the method provided in the above embodiment belong to the same concept, wherein the specific manner in which each module and unit performs operations has been described in detail in the method embodiment and will not be repeated here.

[0139] In another exemplary embodiment, the present application provides an electronic device comprising a processor and a memory, wherein the memory stores computer-readable instructions that, when executed by the processor, implement the aforementioned account recharge prompt method. In this embodiment, the electronic device includes, but is not limited to, a mobile phone, a computer, an intelligent voice interaction device, a smart home appliance, an in-vehicle terminal, and the like.

[0140] Figure 11 A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown.

[0141] It should be noted that Figure 11 The computer system 1000 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0142] like Figure 11 As shown, the computer system 1000 includes a central processing unit (CPU) 1001, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1002 or the program loaded from the storage part 1008 to the random access memory (RAM) 1003, such as executing the information recommendation method in the above embodiment. Various programs and data required for system operation are also stored in the RAM 1003. The CPU 1001, ROM 1002 and RAM 1003 are connected to each other via a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.

[0143] The following components are connected to the I / O interface 1005: an input section 1006 including a keyboard, a mouse, and the like; an output section 1007 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 1008 including a hard disk and the like; and a communication section 1009 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the I / O interface 1005 as needed. Removable media 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 1010 as needed, so that computer programs read therefrom can be installed into the storage section 1008 as needed.

[0144] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 1009, and / or installed from a removable medium 1011. When the computer program is executed by the central processing unit (CPU) 1001, the various functions defined in the system of the present application are executed.

[0145] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable computer program. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0146] It is understandable that in the specific implementation of this application, user information*** and other related data are involved. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0147] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0148] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. In some cases, the names of these units do not constitute limitations on the units themselves.

[0149] Another aspect of the present application provides a computer-readable storage medium having computer-readable instructions stored thereon. When the computer-readable instructions are executed by a processor, the account recharge prompt method according to any one of the above embodiments is implemented.

[0150] Another aspect of the present application provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the account recharge prompt method provided in each of the above embodiments.

[0151] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable computer program. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0152] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0153] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. In some cases, the names of these units do not constitute limitations on the units themselves.

[0154] The above content is only a preferred exemplary embodiment of the present application and is not intended to limit the implementation scheme of the present application. Ordinary technicians in this field can easily make corresponding changes or modifications based on the main ideas and spirit of the present application. Therefore, the scope of protection of the present application shall be based on the scope of protection required by the claims.

Claims

1. A method for prompting an account recharge, characterized in that: include: Based on historical expense consumption data corresponding to an account, predicting estimated expense consumption data corresponding to the account in a future time period; the account includes an advertising account; wherein the estimated expense consumption data includes estimated expense consumption data for each of a plurality of days in the future time period; Determining a supportable time length of the account balance based on the estimated expense consumption data; the supportable time length includes at least one day determined from the plurality of days in descending order of distance from the current time point based on the estimated expense consumption data for each of the plurality of days and the account balance; If the supported time length is less than a preset threshold, obtain the average recharge cycle corresponding to the account, and determine the time length between the current time point and a target time point, where the target time point is the most recent recharge time point from the current time point; If the time between the current time point and the target time point is greater than the average recharge period, sending a recharge reminder message to the account; If the time between the current time point and the target time point is less than or equal to the average recharge period, and the day after the current time point is a holiday, a recharge reminder message is sent to the account; The sending of a recharge reminder message to the account includes: Calculate the sum of the average recharge amount and the average bid price of accounts in the same industry on a month-on-month basis to obtain the month-on-month sum value. The accounts in the same industry are accounts with the same performance ranking as the corresponding industry of the account. N is the value corresponding to the average recharge period. Determine the total amount of estimated cost consumption corresponding to the next N days based on the estimated cost consumption data corresponding to each day in the next N days and the month-on-month sum; A recharge reminder message is generated based on the recommended recharge amount, the estimated supporting time, the account balance and the supporting time, and the recharge reminder message is sent to the account, wherein the recommended recharge amount is the estimated total amount of cost consumption, and the estimated supporting time is the value corresponding to the average recharge cycle.

2. The method according to claim 1, characterized in that The predicting of expected expense consumption data corresponding to the account in a future time period based on the historical expense consumption data corresponding to the account includes: Converting the historical expense consumption data into a historical expense consumption time series; The historical expense consumption time series is input into an account expense consumption prediction model, and the account expense consumption prediction model outputs estimated expense consumption data corresponding to the account in a future time period.

3. The method according to claim 2, characterized in that The converting the historical expense consumption data into a historical expense consumption time series comprises: If the preset historical time period includes the first holiday, the target historical expense consumption data is used as the historical expense consumption data corresponding to the first holiday, and the target historical expense consumption data is the average historical expense consumption data corresponding to a preset length of time near the first holiday within the preset historical time period; Collecting historical expense data corresponding to dates other than the first holiday within the preset historical time period; The historical expense consumption data of each day within the preset historical time period is arranged in chronological order to obtain the historical expense consumption time series.

4. The method according to claim 3, characterized in that The determining of the supportable time length of the account balance according to the estimated expense consumption data includes: If the future time period includes a second holiday, determining the final estimated cost consumption data for the second holiday based on the estimated cost consumption data corresponding to the second holiday and the cost consumption growth rate corresponding to the second holiday, where the cost consumption growth rate corresponding to the second holiday is determined based on the historical cost consumption data corresponding to the first holiday and the target historical cost consumption data; The supportable time length is determined according to the final estimated cost consumption data corresponding to the second holiday, the estimated cost consumption data corresponding to other dates, and the account balance.

5. An account recharge reminder device, characterized in that: include: a prediction module configured to predict, based on historical expense consumption data corresponding to an account, estimated expense consumption data corresponding to the account in a future time period; the account including an advertising account; wherein the estimated expense consumption data includes estimated expense consumption data for each of a plurality of days in the future time period; a determination module, configured to determine a supportable time length of the account balance based on the estimated expense consumption data; the supportable time length includes at least one day determined from the plurality of days in descending order of distance from the current time point based on the estimated expense consumption data for each of the plurality of days and the account balance; an acquisition module, configured to, when the supported time length is less than a preset threshold, acquire an average recharge cycle corresponding to the account and determine a time length between a current time point and a target time point, where the target time point is a recharge time point most recently to the current time point; a sending module, configured to send a recharge reminder message to the account when the time length between the current time point and the target time point is greater than the average recharge period; and to send a recharge reminder message to the account when the time length between the current time point and the target time point is less than or equal to the average recharge period and the day after the current time point is a holiday; The sending of a recharge reminder message to the account includes: Calculate the sum of the average recharge amount and the average bid price of accounts in the same industry on a month-on-month basis to obtain the month-on-month sum value. The accounts in the same industry are accounts with the same performance ranking as the corresponding industry of the account. N is the value corresponding to the average recharge period. Determine the total amount of estimated cost consumption corresponding to the next N days based on the estimated cost consumption data corresponding to each day in the next N days and the month-on-month sum; A recharge reminder message is generated based on the recommended recharge amount, the estimated supporting time, the account balance and the supporting time, and the recharge reminder message is sent to the account, wherein the recommended recharge amount is the estimated total amount of cost consumption, and the estimated supporting time is the value corresponding to the average recharge cycle.

6. An electronic device, characterized in that: include: a memory storing computer-readable instructions; A processor reads computer-readable instructions stored in the memory to execute the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that Computer-readable instructions are stored thereon, and when the computer-readable instructions are executed by a processor of a computer, the computer is caused to execute the method according to any one of claims 1 to 4.

8. A computer program product, characterized in that The method comprises computer instructions carried on a computer-readable storage medium, and when the computer instructions are executed by a processor of a computer, the computer is caused to perform the method according to any one of claims 1 to 4.

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