Communication service payment management method, system, equipment and medium

Abstract

The embodiment of the invention discloses a communication service payment management method and system, equipment and a medium. The method comprises the following steps: determining a real-time balance of a user; if the real-time balance meets a first preset condition, historical activity data of the user is obtained, and the optimal overdraft limit of the user is determined according to the historical activity data; if the real-time balance is smaller than the optimal overdraft limit, determining a recommended payment limit of the user according to the historical activity data; and generating a payment short message based on the recommended payment amount and sending the payment short message to the user. The invention provides a communication service payment management method. And when the user is in arrearage, determining the optimal overdraft quota of the user according to the historical activity data of the user, generating a recommended payment quota for the user, and sending the payment quota to the user through a short message. According to the method, the user is not stopped directly, the recommended payment quota is generated for reference of the user, and the reliable recommended payment quota is provided, so that the stopping payment management of the user is more humanized and intelligent.

Description

A method, system, device and medium for managing payment for communication services Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method, system, device and medium for managing payment for communication services. Background Technology

[0002] In the field of communication services, the management of communication service fees is usually controlled by the basic management logic of suspending service due to overdue payments. That is, when a user's overdue payment reaches a preset suspension threshold, the suspension mechanism will be triggered to shut down the user's communication service.

[0003] Traditional payment management solutions often have many problems. For example, once a user is in arrears, their service is immediately suspended, and they may only discover the suspension when they are out, which affects the user experience. In addition, after a user's service is suspended and they actively pay the bill, they may be suspended again in the short term due to other call charges or other activities, resulting in insufficient balance. This forces the user to pay again, making the user experience extremely poor. Summary of the Invention

[0004] This application addresses some of the deficiencies mentioned in the background art by providing a communication service payment management method, system, device, and medium.

[0005] In a first aspect, this application provides a method for managing payment for communication services, comprising: determining a user's real-time balance; if the real-time balance meets a first predetermined condition, obtaining the user's historical activity data, the historical activity data including the user's historical payment data and the user's historical behavior data; determining the user's optimal overdraft limit based on the historical activity data; if the real-time balance is less than the optimal overdraft limit, determining the user's recommended payment limit based on the historical activity data; and generating a payment SMS message based on the recommended payment limit and sending it to the user.

[0006] In some embodiments of this application, determining a user's optimal overdraft limit based on historical activity data includes: preprocessing the user's historical activity data to obtain input data; inputting the input data into a predetermined model to obtain the prediction result of the predetermined model, wherein the predetermined model is an artificial intelligence model pre-trained based on the user's historical activity data; and determining the user's optimal overdraft limit based on the prediction result.

[0007] In some embodiments of this application, if the real-time balance is less than the optimal overdraft limit, the recommended payment amount for the user is determined based on historical activity data, including: determining the user's maximum monthly consumption within a predetermined period, and determining the user's recommended payment amount based on the real-time balance and the maximum monthly consumption.

[0008] In some embodiments of this application, the method further includes: if the real-time amount is greater than or equal to the optimal overdraft limit, generating a service suspension reminder SMS and a single suspension instruction; after sending the service suspension reminder SMS to the user, sending the single suspension instruction to the communication service control device; the single suspension instruction includes a link to the green payment channel.

[0009] In some embodiments of this application, the method further includes recording the single-stop time corresponding to the user whose single-stop is being processed; if the single-stop time exceeds a preset deadline or the user's real-time balance decreases by a predetermined value after the single-stop, a double-stop command is sent to the communication service control device.

[0010] In some embodiments of this application, the method further includes: identifying the user whose service has been suspended by both the user and a single user; and if the user fails to complete payment by the scheduled time, sending the user a service suspension reminder SMS again.

[0011] In some embodiments of this application, the method further includes: if the user's real-time balance does not meet the first predetermined condition but meets the second predetermined condition, determining the user's recommended payment amount based on the user's average monthly consumption; generating a payment SMS message based on the recommended payment amount and sending it to the user.

[0012] In a second aspect, this application provides a communication service payment management system, comprising: a user balance detection module for determining a user's real-time balance; a user data acquisition module for acquiring the user's historical activity data, including the user's historical payment data and the user's historical behavior data, if the real-time balance meets a first predetermined condition; an optimal overdraft limit determination module for determining the user's optimal overdraft limit based on the historical activity data; a recommended payment limit determination module for determining the user's recommended payment limit based on the historical activity data if the real-time balance is less than the optimal overdraft limit; and a recommended payment information sending module for generating a payment SMS message based on the recommended payment limit and sending it to the user.

[0013] In a third aspect, this application provides a computer device, comprising: at least one processor; and a memory storing computer instructions executable on the processor, wherein the instructions, when executed by the processor, implement the steps of any of the communication service payment management methods described above.

[0014] In a fourth aspect, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of any of the communication service payment management methods described above.

[0015] This application provides a communication service payment management method. When a user is in arrears, the method obtains the user's historical activity data and determines the user's optimal overdraft limit based on this data. When the current balance is less than the optimal overdraft limit, a recommended payment amount is generated for the user and sent to the user via SMS. Instead of directly suspending the user's service, the method generates a recommended payment amount for the user's reference, preventing blind payments. Ultimately, it enables flexible setting of suspension thresholds (optimal overdraft limits) based on different users and provides reliable recommended payment amounts, making service suspension payment management more user-friendly and intelligent. Attached Figure Description

[0016] Figure 1 is a flowchart illustrating a communication service payment management method according to an embodiment of this application; Figure 2 is a structural diagram illustrating a communication service payment management system according to an embodiment of this application; Figure 3 is a structural diagram illustrating a computer device according to an embodiment of this application; Figure 4 is a structural diagram illustrating a computer-readable storage medium according to an embodiment of this application. Detailed Implementation

[0017] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present application, not the entire structure.

[0018] In traditional telecommunications service payment management, the current suspension system filters users based on pre-set arrears thresholds. Once a user's outstanding balance reaches the threshold, service is suspended abruptly, often unexpectedly. Furthermore, even after successful payment, subsequent transactions can trigger suspension again, resulting in a poor user experience.

[0019] As shown in Figure 1, to solve the above problems, in a first aspect, this application provides a communication service payment management method, including: step S1, determining the user's real-time balance; step S2, if the real-time balance meets a first predetermined condition, obtaining the user's historical activity data, which includes the user's historical payment data and the user's historical behavior data; step S3, determining the user's optimal overdraft limit based on the historical activity data; step S4, if the real-time balance is less than the optimal overdraft limit, determining the user's recommended payment limit based on the historical activity data; and step S5, generating a payment SMS based on the recommended payment limit and sending it to the user.

[0020] In this application, the communication service payment management method provided is applied to the communication service provider and is implemented based on data provided by a traditional communication service management platform.

[0021] Real-time balance refers to the current balance of a user provided by the corresponding communication service management platform, which is dynamically changing data. Activity data refers to the user's activity behavior generated during the communication services provided by the communication service provider. This can be call behavior data, such as call duration and number of calls, or payment behavior, such as payment amount and number of payments. It can also be various custom data defined by the communication service provider for management or user classification. That is, the data names and definitions may vary slightly depending on the different communication service providers, but essentially it refers to the user's activity data within the service scope of the communication service provider. Historical activity data refers to the user's activity data within the service scope of the communication service provider over a past period of time. In some embodiments of this application, historical activity data includes consumption ARPU (Average Revenue Per User), payment amount, payment on behalf amount, frequency of family network interaction, amount owed, number of service interruptions, data usage, voice usage, complaint type, etc. In step S1, the real-time balance of the user in the existing user management system of the communication service provider is obtained, which can be obtained from the BOSS (Business & Operation Support System) system.

[0022] In step S2, if it is found that a user's real-time balance is less than a predetermined value, for example, less than 0 (meaning the user is in arrears), then the system will further retrieve all activity data of the corresponding user in arrears over the past few months.

[0023] In step S3, the user's value is assessed based on their historical activity data over the past few months, thereby determining the optimal overdraft limit for that user. For example, the user's average spending over the past three months can be used as the optimal overdraft limit for the user's current spending; alternatively, the optimal overdraft limit can be determined based on the user's average spending over the past three months and call frequency (which could be the frequency of interactions on a family network). The average spending is used as the basis, and a coefficient is determined by comparing the call frequency of the best month with the call frequency over the past three months. The ratio of this coefficient to the average spending is then used as the optimal overdraft limit.

[0024] In some embodiments of this application, user historical activity data can be digitized, and a calculation formula for historical activity data based on multiple dimensions can be determined through digital modeling. For example:

[0025] Where woe represents the optimal overdraft limit, and p represents the probability that the customer's total overdue period exceeds 60 days. The larger the woe value, the larger the optimal overdraft limit that can be granted; the smaller the woe value, the smaller the optimal overdraft limit that can be granted. All woe values ​​are considered as the optimal overdraft limit. This represents the coefficients corresponding to each variable. The table below shows the corresponding variables for the historical activity data.

[0026] After preprocessing the user's recent historical activity data, the optimal overdraft limit for the user is obtained by substituting it into the above formula.

[0027] In step S4, after determining the optimal overdraft limit for the user, it is further determined whether the user's real-time balance is less than the optimal overdraft limit. As mentioned earlier, the user is in arrears at this time. If the user's real-time balance, i.e., the arrears balance, is less than the optimal overdraft limit, then the recommended payment amount for the user is determined based on the user's average monthly consumption in historical activity data or the maximum monthly consumption in recent times. This ensures that after payment, there is a high probability that the user will not incur further arrears due to communication activities in the current month.

[0028] In step S5, after determining the user's recommended payment amount, a corresponding payment notification SMS is generated and sent to the user to remind them to pay according to the recommended amount, thus avoiding the possibility of the user falling into arrears again after payment. This reduces the risk of user service suspension, lowers the frequency of user payments, and improves the user's payment experience.

[0029] In some embodiments of this application, determining a user's optimal overdraft limit based on historical activity data includes: preprocessing the user's historical activity data to obtain input data; inputting the input data into a predetermined model to obtain the prediction result of the predetermined model, wherein the predetermined model is an artificial intelligence model pre-trained based on the user's historical activity data; and determining the user's optimal overdraft limit based on the prediction result.

[0030] In this embodiment, as mentioned above, the formula in step S3 can be pre-trained using an artificial intelligence model, such as a logistic regression model. After obtaining the user's historical activity data, the corresponding historical activity data is preprocessed according to the data format of the training samples used when training the model to obtain the user's input data. The input data is then further input into the pre-trained model to obtain the model's prediction result. Finally, the model's prediction result is converted into the optimal overdraft limit for convenient user payment. For example, after obtaining the output result of the logistic regression model, it is first determined whether the prediction result is positive or negative. If it is negative, the optimal overdraft limit is set to 0; if the prediction result is not an integer of 10, the optimal overdraft limit is set to the nearest multiple of 10, i.e., rounded up to a multiple of 10, to facilitate user top-ups when generating recommended payment limits.

[0031] Furthermore, in some embodiments of this application, the training process of the model used to predict the optimal overdraft limit is as follows: First, 10 features, including historical activity data and overdraft data of 5 million users in a certain region, are sampled and modeled.

[0032] In this dataset, overdraft data is used as the label parameter for each sample, and user's historical activity data is used as the independent variable parameter to construct the training dataset. The independent variable parameters corresponding to the historical activity data are shown in the table below:

[0033] Logistic regression model is used as the algorithm for predicting the optimal overdraft limit:

[0034]

[0035] in 'woe' represents the optimal overdraft limit, and 'p' represents the probability that the customer's total overdue period exceeds 60 days. The larger the 'woe' value, the larger the optimal overdraft limit that can be granted, and the smaller the 'woe' value, the smaller the optimal overdraft limit that can be granted. Therefore, 'woe' is considered the optimal overdraft limit.

[0036] To form a predictive model for the optimal overdraft limit, the woe value of each variable after grouping is used as the input variable. The woe value is a logarithmic value, and the woe value is used to replace the original variable and input into the model.

[0037] Furthermore, after dividing the corresponding sample data into training and test datasets using machine learning tools, the training dataset is then fed into the logistic regression model to estimate the parameters. For example, the `train_test_split` method provided by sklearn can be used to randomly divide the sampled 5 million users into mutually exclusive training and test datasets in an 8:2 ratio.

[0038] The corresponding logistic regression model is obtained, and the corresponding regression coefficients are as follows:

[0039] Based on the above results, the trained model is as follows:

[0040] After determining the historical activity data of users in arrears, the corresponding historical activity data can be preprocessed and then substituted into the corresponding variables to obtain the optimal overdraft limit for the users in arrears.

[0041] Furthermore, when the real-time balance is less than the optimal overdraft limit, it indicates that the user is in arrears but has not reached the threshold for service suspension. To avoid service suspension, the user needs to pay the outstanding amount as soon as possible. The system will then remind the customer of the outstanding amount and urge them to pay and settle the outstanding amount as soon as possible.

[0042] When the real-time balance is greater than the optimal overdraft limit, it indicates that the user has reached the threshold for service suspension due to overdue payments. In order to control the risk of overdue payments and avoid customers accumulating too many overdue payments, it is possible to suspend the service for the user individually.

[0043] In some embodiments of this application, if the real-time balance is less than the optimal overdraft limit, the recommended payment amount for the user is determined based on historical activity data, including: determining the user's maximum monthly consumption within a predetermined period, and determining the user's recommended payment amount based on the real-time balance and the maximum monthly consumption.

[0044] In this embodiment, when a user's real-time balance is less than the optimal overdraft limit, it indicates that the user's current arrears are still within an acceptable range, and there is no need to suspend their service. When generating a recommended payment limit, the absolute value of the user's highest monthly spending over the past few months and their current real-time balance is added together to obtain the user's recommended payment limit. For example, if user A owes 20 yuan, and user A's optimal overdraft limit is 30 yuan, the condition is met. Then, user A's highest monthly spending over the past 3 months is obtained, let's say it's 150 yuan. Therefore, the user's recommended payment limit is 150 + 20 = 170 yuan.

[0045] In some embodiments of this application, the method further includes: if the real-time amount is greater than or equal to the optimal overdraft limit, generating a service suspension reminder SMS and a single suspension instruction; after sending the service suspension reminder SMS to the user, sending the single suspension instruction to the communication service control device; the single suspension instruction includes a link to the green payment channel.

[0046] In this embodiment, communication service control refers to network devices used to control the user's communication services, such as the UDM (Unified Data Management) device in the core network.

[0047] In this embodiment, if the user's real-time balance is greater than or equal to the optimal overdraft limit, it indicates that the user's outstanding balance is too high and no longer within acceptable limits. In this case, a one-way service suspension needs to be implemented for the user. Prior to the suspension, a corresponding one-way service suspension SMS message and a suspension command are generated for the user. The one-way service suspension SMS message includes a recommended payment amount for the user and a link to pay without using data. Furthermore, after sending the service suspension reminder SMS to the user, the suspension command is sent to the service control device.

[0048] In some embodiments of this application, the method further includes recording the single-stop time corresponding to the user whose single-stop is being processed; if the single-stop time exceeds a preset deadline or the user's real-time balance decreases by a predetermined value after the single-stop, a double-stop command is sent to the communication service control device.

[0049] In this embodiment, after a user is suspended, the user information and the start time of the suspension are recorded in the corresponding data table.

[0050] The suspension period for the user is further calculated based on the start time of the suspension and the current time. For example, if user A's suspension started at 00:00 on [date] and the current time is 00:00 on [date], then user A's suspension period is 3 days. If the deadline is 2 days, a double suspension command is sent to the communication service equipment.

[0051] Alternatively, if a user's real-time balance decreases by more than a predetermined amount after a single suspension, a double suspension command is sent to the communication service equipment. For example, if user A's real-time balance decreases by 10 yuan after a single suspension (e.g., when the single suspension is triggered, user A's outgoing call did not stop, and the continued call exceeded 10 yuan in call charges), a double suspension command for user A is sent to the communication service equipment.

[0052] In some embodiments of this application, the method further includes: identifying the user whose service has been suspended by both the user and a single user; and if the user fails to complete payment by the scheduled time, sending the user a service suspension reminder SMS again.

[0053] In this embodiment, users whose accounts are suspended by one or both services are retrieved from the aforementioned data table at a predetermined time each day. If the corresponding user has still not completed payment, a suspension reminder SMS is sent to the user again to remind them to pay. For example, at 10:00 AM every day, a suspension reminder SMS is sent again to users in the data table whose accounts are suspended by one or both services. Similarly, the suspension SMS includes a recommended payment amount and a payment link that grants network access.

[0054] In this embodiment, before suspending services for a specific user, it is first determined which value-added services the user has activated. Then, based on the value-added services activated by the user, a suspension command is sent to the management interface corresponding to the value-added service, restricting service access for the value-added service devices associated with the user. Value-added services refer to services other than the user's basic communication functions that are bound to the user's identity and provided to the user. Examples include broadband services, broadband internet, and IPTV. Furthermore, if the user has activated several value-added services...

[0055] In some embodiments of this application, the method further includes: if the user's real-time balance does not meet the first predetermined condition but meets the second predetermined condition, determining the user's recommended payment amount based on the user's average monthly consumption; generating a payment SMS message based on the recommended payment amount and sending it to the user.

[0056] In this embodiment, when a user's real-time balance is greater than 0 but less than 20% of the average monthly consumption, the user's average monthly consumption in the past few months is determined, and the average monthly consumption is used as the user's recommended payment amount. In this way, a corresponding payment reminder SMS is generated and sent to the corresponding user.

[0057] This application provides a communication service payment management method. When a user is in arrears, the method obtains the user's historical activity data and determines the user's optimal overdraft limit based on this data. When the current balance is less than the optimal overdraft limit, a recommended payment amount is generated for the user and sent to the user via SMS. Instead of directly suspending the user's service, the method generates a recommended payment amount for the user's reference, preventing blind payments. Ultimately, it enables flexible setting of suspension thresholds (optimal overdraft limits) based on different users and provides reliable recommended payment amounts, making service suspension payment management more user-friendly and intelligent.

[0058] As shown in Figure 2, in a second aspect, this application provides a communication service payment management system, comprising: a user balance detection module 1, used to determine the user's real-time balance; a user data acquisition module 2, used to acquire the user's historical activity data if the real-time balance meets a first predetermined condition, the historical activity data including the user's historical payment data and the user's historical behavior data; an optimal overdraft limit determination module 3, used to determine the user's optimal overdraft limit based on the historical activity data; a recommended payment limit determination module 4, used to determine the user's recommended payment limit based on the historical activity data if the real-time balance is less than the optimal overdraft limit; and a recommended payment information sending module 5, used to generate a payment SMS message based on the recommended payment limit and send it to the user.

[0059] In a third aspect, this application provides a computer device, including: at least one processor 31; and a memory 32, the memory 32 storing computer instructions executable on the processor 31, the instructions being executed by the processor 31 to implement the steps of any of the communication service payment management methods described above.

[0060] In a fourth aspect, this application provides a computer-readable storage medium 41 that stores a computer program 42, which, when executed by a processor, implements the steps of any of the communication service payment management methods described above.

[0061] This application provides a communication service payment management method. When a user is in arrears, the method obtains the user's historical activity data and determines the user's optimal overdraft limit based on this data. When the current balance is less than the optimal overdraft limit, a recommended payment amount is generated for the user and sent to the user via SMS. Instead of directly suspending the user's service, the method generates a recommended payment amount for the user's reference, preventing blind payments. Ultimately, it enables flexible setting of suspension thresholds (optimal overdraft limits) based on different users and provides reliable recommended payment amounts, making service suspension payment management more user-friendly and intelligent.

[0062] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0063] Computer instructions include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. Computer-readable media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in computer-readable media can be appropriately added to or removed according to the requirements of legislation and patent practice in a jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0064] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments in this specification are not limited to the described order of actions, because according to the embodiments in this specification, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments in this specification.

[0065] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0066] The preferred embodiments disclosed above are merely illustrative of this specification. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to specific implementations. Clearly, many modifications and variations can be made based on the embodiments described in this specification. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the embodiments, thereby enabling those skilled in the art to better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. A method for managing payment for communication services, characterized in that, include: Determine the user's real-time balance; if the real-time balance meets a first predetermined condition, obtain the user's historical activity data, which includes the user's historical payment data and the user's historical behavior data; determine the user's optimal overdraft limit based on the historical activity data; if the real-time balance is less than the optimal overdraft limit, determine the user's recommended payment amount based on the historical activity data; generate a payment SMS based on the recommended payment amount and send it to the user.

2. The method according to claim 1, characterized in that, The step of determining the user's optimal overdraft limit based on the historical activity data includes: preprocessing the user's historical activity data to obtain input data; inputting the input data into a predetermined model to obtain the prediction result of the predetermined model, wherein the predetermined model is an artificial intelligence model pre-trained based on the user's historical activity data; and determining the user's optimal overdraft limit based on the prediction result.

3. The method according to claim 1, characterized in that, If the real-time balance is less than the optimal overdraft limit, determining the user's recommended payment amount based on the historical activity data includes: determining the user's maximum monthly consumption within a predetermined time period, and determining the user's recommended payment amount based on the real-time balance and the maximum monthly consumption.

4. The method according to claim 1, characterized in that, The method further includes: if the real-time amount is greater than or equal to the optimal overdraft limit, generating a service suspension reminder SMS and a single suspension instruction; after sending the service suspension reminder SMS to the user, sending the single suspension instruction to the communication service control device; the single suspension instruction includes a link to the green payment channel.

5. The method according to claim 4, characterized in that, The method further includes: recording the single-stop time corresponding to the user whose single-stop is applied; if the single-stop time exceeds a preset deadline or the user's real-time balance decreases by a predetermined value after the single-stop, then sending a double-stop instruction to the communication service control device.

6. The method according to claim 5, characterized in that, The method further includes: identifying users who have been suspended by both the service provider and the user, or by only the service provider; and if the user fails to pay the bill by the scheduled time, sending the suspension reminder SMS to the user again.

7. The method according to claim 1, characterized in that, The method further includes: if the user's real-time balance does not meet the first predetermined condition but meets the second predetermined condition, determining the user's recommended payment amount based on the user's average monthly consumption; and generating a payment SMS message based on the recommended payment amount and sending it to the user.

8. A communication service payment management system, characterized in that, include: The user balance detection module is used to determine the user's real-time balance; the user data acquisition module is used to acquire the user's historical activity data if the real-time balance meets a first predetermined condition, the historical activity data including the user's historical payment data and the user's historical behavior data; the optimal overdraft limit determination module is used to determine the user's optimal overdraft limit based on the historical activity data. The recommended payment amount determination module is used to determine the user's recommended payment amount based on the historical activity data if the real-time balance is less than the optimal overdraft amount. The recommended payment information sending module is used to generate a payment SMS message based on the recommended payment amount and send it to the user.

9. A computer device, characterized in that, include: At least one processor; And a memory storing computer instructions executable on the processor, which, when executed by the processor, implement the steps of the method according to any one of claims 1-6.

10. A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method according to any one of claims 1-6.

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