Call-out sensitive waybill generation method, device, equipment, medium and program product

Abstract

The embodiment of the invention discloses an outbound sensitive waybill generation method and device, equipment, a medium and a program product. A specific embodiment of the method comprises the following steps: acquiring a waybill information set; for each piece of waybill information in the waybill information set, executing the following generation steps: extracting waybill feature data corresponding to the waybill information; inputting the waybill feature data into a pre-trained outbound customer complaint information generation model to generate outbound customer complaint information; inputting the waybill feature data into a pre-trained non-outbound customer complaint information generation model to generate non-outbound customer complaint information; and screening out at least one piece of outbound sensitive waybill information from the waybill information set according to the obtained outbound customer complaint information set and the obtained non-outbound customer complaint information set. The implementation mode is related to artificial intelligence, and at least one piece of outbound sensitive waybill information is accurately and efficiently determined from the waybill information set, so that the subsequent waybill distribution service level is improved in a targeted manner.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to a method, device, equipment, medium, and program product for generating an outbound call-sensitive waybill. Background Art

[0002] At present, during the delivery and collection process of logistics terminals, customers are dissatisfied with the quality of delivery services, which will lead to certain customer complaints and even worse customer churn. For the delivery of waybills, the usual approach is to use a one-size-fits-all or point-to-point solution (for example, all waybills are processed by outbound calls in the scenario where the person who signed for the waybill is not the person himself) to execute the delivery of waybills.

[0003] However, the inventors have found that when the above method is adopted, the following technical problems often occur:

[0004] Frequent outbound calls seriously affect customer experience and the work efficiency of delivery personnel, and are likely to generate more customer complaints, resulting in a poor service image. In addition, frequent outbound calls generate higher communication costs.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. Summary of the invention

[0006] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0007] Some embodiments of the present disclosure propose methods, devices, equipment, media and program products for generating outbound call-sensitive waybills to solve the technical problems mentioned in the above background technology section.

[0008] In a first aspect, some embodiments of the present disclosure provide a method for generating an outbound call-sensitive waybill, comprising: obtaining a waybill information set; for each waybill information in the waybill information set, performing the following generation steps: extracting waybill feature data corresponding to the waybill information; inputting the waybill feature data into a pre-trained outbound customer complaint information generation model to generate outbound customer complaint information; inputting the waybill feature data into a pre-trained non-outbound customer complaint information generation model to generate non-outbound customer complaint information; and based on the obtained outbound customer complaint information set and the non-outbound customer complaint information set, filtering out at least one outbound call-sensitive waybill information from the waybill information set.

[0009] Optionally, the method of filtering out at least one outbound-sensitive waybill information from the waybill information set based on the obtained outbound customer complaint information set and the non-outbound customer complaint information set comprises: for each waybill information in the waybill information set, determining the information difference between the outbound customer complaint information corresponding to the waybill information and the non-outbound customer complaint information corresponding to the waybill information as customer complaint-sensitive information; filtering out customer complaint-sensitive information whose corresponding numerical values ​​are within the first predetermined number from the obtained customer complaint-sensitive information set to obtain at least one customer complaint-sensitive information; and determining at least one waybill information corresponding to the at least one customer complaint-sensitive information as at least one outbound-sensitive waybill information.

[0010] Optionally, based on the obtained outbound customer complaint information set and the non-outbound customer complaint information set, at least one outbound sensitive waybill information is filtered out from the waybill information set, including: for each waybill information in the waybill information set, based on the outbound customer complaint information and the non-outbound customer complaint information corresponding to the waybill information, determining the outbound customer complaint type information corresponding to the waybill information; and filtering out from the waybill information set at least one waybill information whose corresponding outbound customer complaint type information is the target outbound customer complaint type information, as at least one outbound sensitive waybill information.

[0011] Optionally, the method further includes: sending a target waybill operation request for the at least one outbound call sensitive waybill information to the target delivery terminal, so that personnel corresponding to the target delivery terminal and users corresponding to the at least one outbound call sensitive waybill information can perform outbound call control operations.

[0012] Optionally, the method also includes: for each outbound call sensitive waybill information in the at least one outbound call sensitive waybill information, performing the following determination steps: determining the object complaint information of the waybill object corresponding to the outbound call sensitive waybill information; in response to determining that the object complaint information represents that the waybill object has historical complaint behavior, obtaining historical complaint event information corresponding to the waybill object; generating waybill communication method information based on the historical complaint event information; in response to determining that the object complaint information represents that the waybill object has no historical complaint behavior, determining the outbound call sensitive waybill feature data corresponding to the outbound call sensitive waybill information; inputting the outbound call sensitive waybill feature data into the outbound call communication information generation model to generate the outbound call communication information; determining the waybill communication method information based on the outbound call communication information; and performing waybill communication processing for the at least one outbound call sensitive waybill information based on the obtained at least one waybill communication method information.

[0013] Optionally, the outbound customer complaint information generation model and the non-outbound customer complaint information generation model are trained by the following steps: obtaining an outbound waybill information set and a non-outbound waybill information set; extracting the outbound waybill feature data corresponding to each outbound waybill information in the outbound waybill information set to obtain an outbound waybill feature data set, and extracting the non-outbound waybill feature data corresponding to each non-outbound waybill data in the non-outbound waybill information set to obtain a non-outbound waybill feature data set; performing model training on the initial outbound customer complaint information generation model based on the outbound waybill feature data set to obtain an outbound customer complaint information generation model; performing model training on the initial non-outbound customer complaint information generation model based on the non-outbound waybill feature data set to obtain a non-outbound customer complaint information generation model.

[0014] In a second aspect, some embodiments of the present disclosure provide an outbound call-sensitive waybill generation device, comprising: an acquisition unit, configured to acquire a waybill information set; an execution unit, configured to perform the following generation steps for each waybill information in the waybill information set: extracting waybill feature data corresponding to the waybill information; inputting the waybill feature data into a pre-trained outbound customer complaint information generation model to generate outbound customer complaint information; inputting the waybill feature data into a pre-trained non-outbound customer complaint information generation model to generate non-outbound customer complaint information; and a screening unit, configured to screen out at least one outbound call-sensitive waybill information from the waybill information set based on the obtained outbound customer complaint information set and the non-outbound customer complaint information set.

[0015] Optionally, the screening unit can be configured to: for each waybill information in the waybill information set, determine the information difference between the outbound customer complaint information corresponding to the waybill information and the non-outbound customer complaint information corresponding to the waybill information as customer complaint sensitive information; screen out customer complaint sensitive information whose corresponding numerical values ​​are within the first predetermined number from the obtained customer complaint sensitive information set to obtain at least one customer complaint sensitive information; and determine at least one waybill information corresponding to the at least one customer complaint sensitive information as at least one outbound sensitive waybill information.

[0016] Optionally, the screening unit can be configured to: for each waybill information in the waybill information set, determine the outbound customer complaint type information corresponding to the waybill information based on the outbound customer complaint information and non-outbound customer complaint information corresponding to the waybill information; and screen out at least one waybill information whose corresponding outbound customer complaint type information is the target outbound customer complaint type information from the waybill information set as at least one outbound sensitive waybill information.

[0017] Optionally, the device also includes: sending a target waybill operation request for the at least one outbound call sensitive waybill information to the target delivery terminal, so that the personnel corresponding to the target delivery terminal and the user corresponding to the at least one outbound call sensitive waybill information can perform outbound call control operations.

[0018] Optionally, the device also includes: for each outbound call sensitive waybill information in the at least one outbound call sensitive waybill information, performing the following determination steps: determining the object complaint information of the waybill object corresponding to the outbound call sensitive waybill information; in response to determining that the object complaint information represents that the waybill object has historical complaint behavior, obtaining historical complaint event information corresponding to the waybill object; generating waybill communication method information based on the historical complaint event information; in response to determining that the object complaint information represents that the waybill object has no historical complaint behavior, determining the outbound call sensitive waybill feature data corresponding to the outbound call sensitive waybill information; inputting the outbound call sensitive waybill feature data into the outbound call communication information generation model to generate the outbound call communication information; determining the waybill communication method information based on the outbound call communication information; and performing waybill communication processing for the at least one outbound call sensitive waybill information based on the obtained at least one waybill communication method information.

[0019] Optionally, the outbound customer complaint information generation model and the non-outbound customer complaint information generation model are trained by the following steps: obtaining an outbound waybill information set and a non-outbound waybill information set; extracting the outbound waybill feature data corresponding to each outbound waybill information in the outbound waybill information set to obtain an outbound waybill feature data set, and extracting the non-outbound waybill feature data corresponding to each non-outbound waybill data in the non-outbound waybill information set to obtain a non-outbound waybill feature data set; performing model training on the initial outbound customer complaint information generation model based on the outbound waybill feature data set to obtain an outbound customer complaint information generation model; performing model training on the initial non-outbound customer complaint information generation model based on the non-outbound waybill feature data set to obtain a non-outbound customer complaint information generation model.

[0020] In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner in the first aspect.

[0021] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner in the first aspect is implemented.

[0022] In a fifth aspect, some embodiments of the present disclosure provide a computer program product, including a computer program, which implements the method described in any implementation manner in the above-mentioned first aspect when executed by a processor.

[0023] The above-mentioned embodiments of the present disclosure have the following beneficial effects: through the outbound call sensitive waybill generation method of some embodiments of the present disclosure, at least one outbound call sensitive waybill information is accurately and efficiently determined from the waybill information set to improve the delivery service level of subsequent waybills in a targeted manner. Specifically, the reason for the poor delivery service level is that frequent outbound calls seriously affect the customer experience and the work efficiency of the delivery personnel, and there is a high probability that more customer complaints will be generated, resulting in an image of poor service level. In addition, frequent outbound calls generate higher communication costs. Based on this, the outbound call sensitive waybill generation method of some embodiments of the present disclosure, first, obtains the waybill information set to facilitate the subsequent delivery of the corresponding waybill set. In addition, it provides data basis for the generation of subsequent outbound customer complaint information and non-outbound customer complaint information. Then, for each waybill information in the waybill information set, the following generation steps are performed: the first step is to extract the waybill feature data corresponding to the waybill information, so as to be used as feature data for the waybill, so as to input it into the model, so that the model can learn more feature information. In the second step, the waybill feature data is input into a pre-trained outbound customer complaint information generation model to accurately generate outbound customer complaint information. Among them, the outbound customer complaint information can accurately reflect the probability of customer complaints against the waybill information under the premise of outbound calls. Third, the waybill feature data is input into a pre-trained non-outbound customer complaint information generation model to accurately generate non-outbound customer complaint information. Among them, the non-outbound customer complaint information can accurately reflect the probability of customer complaints against the waybill information under the premise of non-outbound calls. Finally, based on the obtained outbound customer complaint information set and non-outbound customer complaint information set, at least one outbound sensitive waybill information can be accurately screened out from the waybill information set. In summary, through the outbound customer complaint information generation model and the non-outbound customer complaint information generation model, the probability of customer complaints under outbound call conditions and the probability of customer complaints under non-outbound call conditions can be determined respectively, and the customer complaints of the waybill information can be considered from multiple angles and perspectives. Therefore, at least one outbound call sensitive waybill information can be accurately screened out based on the outbound customer complaint information set and the non-outbound customer complaint information set. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0025] Figure 1 is a schematic diagram of an application scenario of the method for generating an outbound call sensitive waybill according to some embodiments of the present disclosure;

[0026] Figure 2 is a flow chart of some embodiments of the method for generating an outbound call sensitive waybill according to the present disclosure;

[0027] Figure 3 is a flow chart of other embodiments of the method for generating an outbound call sensitive waybill according to the present disclosure;

[0028] Figure 4 It is a structural schematic diagram of some embodiments of the outbound call sensitive waybill generation device according to the present disclosure;

[0029] Figure 5 It is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0030] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0031] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0032] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0033] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0034] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0035] With regard to the collection, storage, and use of user personal information (such as waybill information) involved in this disclosure, before performing the corresponding operations, the relevant organizations or individuals shall fulfill their obligations, including conducting personal information security impact assessments, fulfilling the obligation to inform the personal information subject, and obtaining the authorization and consent of the personal information subject in advance.

[0036] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0037] Figure 1It is a schematic diagram of an application scenario of the method for generating an outbound call-sensitive waybill according to some embodiments of the present disclosure.

[0038] exist Figure 1 In the application scenario, first, the electronic device 101 can obtain the waybill information set 102. In this application scenario, the waybill information set 102 may include: the first waybill information 1021, the second waybill information 1022, the third waybill information 1023 and the fourth waybill information 1024. Then, for each waybill information in the waybill information set 102, the electronic device 101 can perform the following generation steps: the first step is to extract the waybill feature data corresponding to the waybill information. In this application scenario, the first waybill feature data 1081 corresponding to the first waybill information 1021 is extracted. The second waybill feature data 1082 corresponding to the second waybill information 1022 is extracted. The third waybill feature data 1083 corresponding to the third waybill information 1023 is extracted. The fourth waybill feature data 1084 corresponding to the fourth waybill information 1024 is extracted. The second step is to input the waybill feature data into the pre-trained outbound customer complaint information generation model 103 to generate outbound customer complaint information. In this application scenario, the first waybill feature data 1081 is input into the outbound customer complaint information generation model 103 to obtain the first outbound customer complaint information 1041. The second waybill feature data 1082 is input into the outbound customer complaint information generation model 103 to obtain the second outbound customer complaint information 1042. The third waybill feature data 1083 is input into the outbound customer complaint information generation model 103 to obtain the third outbound customer complaint information 1043. The fourth waybill feature data 1084 is input into the outbound customer complaint information generation model 103 to obtain the fourth outbound customer complaint information 1044. In the third step, the waybill feature data is input into the pre-trained non-outbound customer complaint information generation model 105 to generate non-outbound customer complaint information. In this application scenario, the first waybill feature data 1081 is input into the non-outbound customer complaint information generation model 105 to obtain the second outbound customer complaint information 1061. The second waybill feature data 1082 is input into the non-outbound customer complaint information generation model 105 to obtain the second non-outbound customer complaint information 1062. The third waybill feature data 1083 is input into the non-outbound customer complaint information generation model 105 to obtain the third non-outbound customer complaint information 1063. The fourth waybill feature data 1084 is input into the non-outbound customer complaint information generation model 105 to obtain the fourth non-outbound customer complaint information 1064. Finally, the electronic device 101 can filter out at least one outbound call sensitive waybill information 107 from the waybill information set 102 according to the obtained outbound customer complaint information set 104 and the non-outbound customer complaint information set 106. In this application scenario, the at least one outbound call sensitive waybill information 107 may include: the first waybill information 1021 and the second waybill information 1022.

[0039] It should be noted that the electronic device 101 can be hardware or software. When the electronic device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or it can be implemented as a single server or a single terminal device. When the electronic device is embodied as software, it can be installed in the hardware devices listed above. It can be implemented as multiple software or software modules for providing distributed services, for example, or it can be implemented as a single software or software module. No specific limitation is made here.

[0040] It should be understood that Figure 1 The number of electronic devices in the embodiment is only for illustration. Any number of electronic devices may be provided according to implementation requirements.

[0041] Continue to refer Figure 2 , shows a process 200 of some embodiments of the method for generating an outbound call sensitive waybill according to the present disclosure. The method for generating an outbound call sensitive waybill comprises the following steps:

[0042] Step 201, obtain a waybill information set.

[0043] In some embodiments, the execution subject of the above-mentioned outbound call sensitive waybill generation method (for example Figure 1 The electronic device 101 shown can obtain the waybill information set through a wired connection or a wireless connection. The waybill information can be the order information of the waybill. The waybill can be various types of delivery orders. For example, the waybill can be a fresh food express waybill. The waybill information can represent the waybill identity information of the waybill. For example, the waybill information can include the waybill number.

[0044] Step 202: for each waybill information in the waybill information set, perform the following generation steps:

[0045] Step 2021, extracting the waybill characteristic data corresponding to the waybill information.

[0046] In some embodiments, the above-mentioned execution entity can extract the waybill feature data corresponding to the waybill information. Among them, the waybill feature data can be the feature content data of the waybill corresponding to the waybill information. In practice, the waybill feature data can include data of multiple feature dimensions. For example, the waybill feature data includes: customer dimension data, waybill basic attribute dimension data, recipient address road area dimension data, and courier dimension data. Customer dimension data may include: call preference data, order frequency data, receipt type distribution data, number of addresses, customer complaints, and customer complaint type distribution. The waybill basic attribute dimension data may include: destination, carrier, area, order type, channel, business attributes, transportation method, whether fresh, delivery products, weight volume and distance. The consignee address road area dimension feature data includes: road area type, road area area, number of customer complaints in the road area, customer complaint type distribution, order quantity, number of recipients, and number of transportation personnel. The courier dimension data may include: personnel nature, rank, gender, age, length of service, education level, business score, responsible route area, route type, number of successfully delivered orders, distribution of delivery order types, and number of customer complaints.

[0047] As an example, the above-mentioned execution entity can perform semantic extraction on the waybill content corresponding to the waybill information to obtain waybill feature data.

[0048] Step 2022, input the waybill feature data into a pre-trained outbound customer complaint information generation model to generate outbound customer complaint information.

[0049] In some embodiments, the above-mentioned execution entity may input the waybill feature data into a pre-trained outbound customer complaint information generation model to generate outbound customer complaint information. Among them, the outbound customer complaint information generation model may be a neural network model for generating outbound customer complaint information. For example, the outbound customer complaint information may be the probability information of the waybill being complained by the customer under the premise of an outbound call. That is, the above-mentioned outbound customer complaint information may be a numerical value between 0 and 1. In practice, the outbound customer complaint information generation model may be a classification model. For example, the outbound customer complaint information generation model may be a LightGBM (Light Gradient Boosting Machine) model.

[0050] Step 2023: input the waybill feature data into a pre-trained model for generating uncalled customer complaints information to generate uncalled customer complaints information.

[0051] In some embodiments, the above-mentioned execution entity may input the waybill feature data into a pre-trained model for generating customer complaint information without outbound calls to generate customer complaint information without outbound calls. Among them, the model for generating customer complaint information without outbound calls may be a neural network model for generating customer complaint information without outbound calls. For example, customer complaint information without outbound calls may be the probability information of a waybill being complained by a customer without outbound calls. That is, the above-mentioned customer complaint information without outbound calls may be a numerical value between 0 and 1. In practice, the model for generating customer complaint information without outbound calls may be a classification model. For example, the model for generating customer complaint information without outbound calls may be a LightGBM (Light Gradient Boosting Machine) model.

[0052] In some optional implementations of some embodiments, the outbound customer complaint information generation model and the non-outbound customer complaint information generation model are trained by the following steps:

[0053] The first step is to obtain an outbound waybill information set and a non-outbound waybill information set. Among them, the outbound waybill information can be the waybill information for which an outbound call operation has been performed in advance. The outbound waybill information includes: the waybill content information of the outbound waybill and the customer complaint information corresponding to the outbound waybill. The non-outbound waybill information can be the waybill information for which no outbound call operation has been performed in advance. The non-outbound waybill information includes: the waybill content information of the non-outbound waybill and the customer complaint information corresponding to the non-outbound waybill.

[0054] The second step is to extract the outbound waybill feature data corresponding to each outbound waybill information in the outbound waybill information set to obtain an outbound waybill feature data set, and extract the non-outbound waybill feature data corresponding to each non-outbound waybill data in the non-outbound waybill information set to obtain a non-outbound waybill feature data set. Specifically, the outbound waybill feature data and the non-outbound waybill feature data can refer to the relevant explanation of the waybill feature data.

[0055] The third step is to train the initial outbound customer complaint information generation model based on the outbound waybill feature data set to obtain the outbound customer complaint information generation model.

[0056] As an example, the execution entity may use the outbound waybill feature data set as the first training data set to perform model training on the initial outbound customer complaint information generation model to obtain the outbound customer complaint information generation model.

[0057] As another example, the above-mentioned execution entity can use the outbound waybill feature data set and the non-outbound waybill feature data set as comparative learning training data sets to perform model training on the initial outbound customer complaint information generation model to obtain the outbound customer complaint information generation model.

[0058] The fourth step is to train the initial model for generating customer complaints of uncalled routes based on the feature data set of uncalled waybills, so as to obtain the model for generating customer complaints of uncalled routes.

[0059] As an example, the above-mentioned execution entity can use the feature data set of uncalled waybills as the second training data set to perform model training on the initial uncalled customer complaint information generation model to obtain the uncalled customer complaint information generation model.

[0060] As another example, the above-mentioned execution entity can use the outbound call waybill feature data set and the non-outbound call waybill feature data set as comparative learning training data sets to perform model training on the initial non-outbound call customer complaint information generation model to obtain the non-outbound call customer complaint information generation model.

[0061] Step 203: at least one outbound call sensitive waybill information is screened out from the waybill information set according to the obtained outbound customer complaint information set and the non-outbound customer complaint information set.

[0062] In some embodiments, the execution subject may filter out at least one outbound call sensitive waybill information from the waybill information set based on the obtained outbound customer complaint information set and the non-outbound customer complaint information set. The outbound call sensitive waybill information may be waybill information of waybills that are sensitive to outbound call operations. That is, waybill information that the corresponding customer may complain about for outbound call operations.

[0063] As an example, first, the execution subject may arrange the waybill information set according to the order of outbound customer complaint information from large to small to obtain a waybill information sequence. Then, according to the order of non-outbound customer complaint information from large to small, the same and adjacent waybill information groups in the waybill information sequence are rearranged to obtain a rearranged waybill information sequence. Finally, a predetermined number of waybill information located at the back end of the sequence in the rearranged waybill information sequence is determined as at least one outbound sensitive waybill information.

[0064] In some optional implementations of some embodiments, the step of filtering out at least one outbound call sensitive waybill information from the waybill information set according to the obtained outbound customer complaint information set and the non-outbound customer complaint information set may include the following steps:

[0065] In the first step, for each waybill information in the waybill information set, the execution entity may determine the information difference between the outbound customer complaint information corresponding to the waybill information and the non-outbound customer complaint information corresponding to the waybill information as customer complaint sensitive information.

[0066] As an example, for each waybill information in the waybill information set, the execution entity may subtract the outbound customer complaint information from the non-outbound customer complaint information to obtain the information difference as the customer complaint sensitive information.

[0067] In the second step, the execution subject may select the customer complaint sensitive information whose corresponding value is in the first predetermined number from the obtained customer complaint sensitive information set to obtain at least one customer complaint sensitive information. For example, the predetermined number may be half of the number of customer complaint sensitive information included in the customer complaint sensitive information set.

[0068] In a third step, the execution entity may determine the at least one waybill information corresponding to the at least one customer complaint sensitive information as at least one outbound call sensitive waybill information.

[0069] In some optional implementations of some embodiments, the step of filtering out at least one outbound call sensitive waybill information from the waybill information set according to the obtained outbound customer complaint information set and the non-outbound customer complaint information set may include the following steps:

[0070] The first step is to determine the outbound customer complaint type information corresponding to the waybill information for each waybill information in the waybill information set, based on the outbound customer complaint information and the non-outbound customer complaint information corresponding to the waybill information. Among them, the outbound customer complaint type information can be the customer complaint type information corresponding to the outbound customer complaint. Specifically, the outbound customer complaint type information can include: type information indicating that customers will not complain if an outbound call is made in advance, type information indicating that customers will complain if no outbound call is made in advance and that outbound calling in advance can avoid customer complaints, information indicating that customers will complain regardless of whether an outbound call is made, and type information indicating that customers have not been complained about in advance for outbound calls, but will be complained about if an outbound call is made.

[0071] In the second step, at least one waybill information corresponding to the outbound customer complaint type information as the target outbound customer complaint type information is selected from the waybill information set as at least one outbound sensitive waybill information. The target outbound customer complaint type may be a type indicating that the customer will complain if no outbound call is made in advance and that the outbound call in advance can avoid the customer complaint.

[0072] In some optional implementations of some embodiments, after step 203, the steps further include:

[0073] In the first step, for each outbound call sensitive waybill information in the at least one outbound call sensitive waybill information, the following determination steps are performed:

[0074] Sub-step 1: determining the object complaint information of the waybill object corresponding to the outbound call sensitive waybill information. The waybill object may be the object receiving the waybill. The object complaint information may be the complaint record information of the waybill receiving object against the delivery personnel.

[0075] Sub-step 2, in response to determining that the object complaint information indicates that the waybill object has a historical complaint behavior, obtain the historical complaint event information corresponding to the waybill object. The historical complaint behavior may be a complaint behavior that has occurred in the past. The historical complaint event information may be the event record information corresponding to the historical complaint event. In practice, the historical complaint event information may include: complaint object information, complaint time information, complaint reason, and complaint method.

[0076] Sub-step 3, generating waybill communication method information based on the historical complaint event information. The waybill communication method information may be waybill communication method information. The waybill communication method may be a communication method between a delivery object and a to-be-received object. For example, the waybill communication method includes: an outbound call communication method and a text message communication method.

[0077] As an example, first, the execution entity may determine the priority waybill communication method information based on the complaint reasons included in the historical complaint event information. Then, the secondary waybill communication method information is generated. Finally, the priority waybill communication method information and the secondary waybill communication method information are combined to generate the waybill communication method information.

[0078] Sub-step 4, in response to determining that the object complaint information indicates that the waybill object has no historical complaint behavior, determining the outbound call sensitive waybill feature data corresponding to the outbound call sensitive waybill information.

[0079] As an example, the above-mentioned execution entity can determine the outbound call sensitive waybill feature data corresponding to the outbound call sensitive waybill information by feature extraction.

[0080] Sub-step 5, inputting the outbound call sensitive waybill characteristic data into the outbound call communication information generation model to generate the outbound call communication information. The outbound call communication information generation model may be a neural network model for generating outbound call communication information. In practice, the outbound call communication information generation model may be a multi-layer serially connected recurrent neural network model. The outbound call communication information may be the outbound call selection information corresponding to the outbound call sensitive waybill without making a complaint. The outbound call selection information includes: selection information indicating that an outbound call is made to the object corresponding to the outbound call sensitive waybill, and selection information indicating that an outbound call is not made to the object corresponding to the outbound call sensitive waybill.

[0081] Sub-step 6, determining the waybill communication method information based on the outbound call communication information.

[0082] As an example, in response to determining that the outbound call communication information represents selection information for making an outbound call to an outbound call-sensitive waybill corresponding object, the method information corresponding to the waybill communication method of the default outbound call communication is determined as the waybill communication method information. In response to determining that the outbound call communication information represents selection information for not making an outbound call to an outbound call-sensitive waybill corresponding object, information for not making waybill communication is determined as the waybill communication method information.

[0083] In the second step, according to the obtained at least one waybill communication mode information, a waybill communication process is performed for the at least one outbound call sensitive waybill information.

[0084] As an example, the above-mentioned execution subject can execute the waybill communication processing for the at least one outbound call sensitive waybill information according to at least one waybill communication method corresponding to the at least one waybill communication method information.

[0085] The above-mentioned embodiments of the present disclosure have the following beneficial effects: through the outbound call sensitive waybill generation method of some embodiments of the present disclosure, at least one outbound call sensitive waybill information is accurately and efficiently determined from the waybill information set to improve the delivery service level of subsequent waybills in a targeted manner. Specifically, the reason for the poor delivery service level is that frequent outbound calls seriously affect the customer experience and the work efficiency of the delivery personnel, and there is a high probability that more customer complaints will be generated, resulting in an image of poor service level. In addition, frequent outbound calls generate higher communication costs. Based on this, the outbound call sensitive waybill generation method of some embodiments of the present disclosure, first, obtains the waybill information set to facilitate the subsequent delivery of the corresponding waybill set. In addition, it provides data basis for the generation of subsequent outbound customer complaint information and non-outbound customer complaint information. Then, for each waybill information in the waybill information set, the following generation steps are performed: the first step is to extract the waybill feature data corresponding to the waybill information, so as to be used as feature data for the waybill, so as to input it into the model, so that the model can learn more feature information. In the second step, the waybill feature data is input into a pre-trained outbound customer complaint information generation model to accurately generate outbound customer complaint information. Among them, the outbound customer complaint information can accurately reflect the probability of customer complaints against the waybill information under the premise of outbound calls. Third, the waybill feature data is input into a pre-trained non-outbound customer complaint information generation model to accurately generate non-outbound customer complaint information. Among them, the non-outbound customer complaint information can accurately reflect the probability of customer complaints against the waybill information under the premise of non-outbound calls. Finally, based on the obtained outbound customer complaint information set and non-outbound customer complaint information set, at least one outbound sensitive waybill information can be accurately screened out from the waybill information set. In summary, through the outbound customer complaint information generation model and the non-outbound customer complaint information generation model, the probability of customer complaints under outbound call conditions and the probability of customer complaints under non-outbound call conditions can be determined respectively, and the customer complaints of the waybill information can be considered from multiple angles and perspectives. Therefore, at least one outbound call sensitive waybill information can be accurately screened out based on the outbound customer complaint information set and the non-outbound customer complaint information set.

[0086] Further references Figure 3 , shows a process 300 of another embodiment of the method for generating an outbound call sensitive waybill according to the present disclosure. The method for generating an outbound call sensitive waybill comprises the following steps:

[0087] Step 301, obtain a waybill information set.

[0088] Step 302: for each waybill information in the waybill information set, perform the following generation steps:

[0089] Step 3021, extracting the waybill feature data corresponding to the waybill information.

[0090] Step 3022, input the waybill feature data into a pre-trained outbound customer complaint information generation model to generate outbound customer complaint information.

[0091] Step 3023, input the waybill feature data into a pre-trained model for generating information on customer complaints without outbound calls, so as to generate information on customer complaints without outbound calls.

[0092] Step 303: at least one outbound call sensitive waybill information is screened out from the waybill information set according to the obtained outbound customer complaint information set and the non-outbound customer complaint information set.

[0093] In some embodiments, the specific implementation of steps 301-303 and the technical effects thereof can be referred to in Figure 2 The steps 201-203 in the corresponding embodiment are not described in detail here.

[0094] Step 304, sending a target waybill operation request for the at least one outbound call sensitive waybill information to the target delivery terminal, so that the personnel corresponding to the target delivery terminal and the user corresponding to the at least one outbound call sensitive waybill information can perform outbound call control operations.

[0095] In some embodiments, an execution entity (e.g. Figure 1 The electronic device 101 shown can send a target waybill operation request for the at least one outbound call sensitive waybill information to the target delivery terminal, so that the corresponding personnel of the target delivery terminal and the corresponding user of the at least one outbound call sensitive waybill information can perform outbound call control operations. Among them, the outbound call control operation can be an operation to control outbound call operations.

[0096] from Figure 3 It can be seen that Figure 2 Compared with the description of some corresponding embodiments, Figure 3 In some corresponding embodiments, the process 300 of the outbound call-sensitive waybill generation method can not only greatly improve the delivery service level but also reduce the delivery cost by performing an outbound call control operation on at least one waybill corresponding to at least one outbound call-sensitive waybill information.

[0097] Further references Figure 4 As an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of an outbound call sensitive waybill generation device, and these device embodiments are similar to Figure 2 Corresponding to the method embodiments shown, the outbound call-sensitive waybill generation device can be specifically applied to various electronic devices.

[0098] like Figure 4As shown, an outbound call sensitive waybill generation device 400 includes: an acquisition unit 401, an execution unit 402 and a screening unit 403. The acquisition unit 401 is configured to acquire a waybill information set; the execution unit 402 is configured to perform the following generation steps for each waybill information in the waybill information set: extract the waybill feature data corresponding to the waybill information; input the waybill feature data into a pre-trained outbound customer complaint information generation model to generate outbound customer complaint information; input the waybill feature data into a pre-trained non-outbound customer complaint information generation model to generate non-outbound customer complaint information; the screening unit 403 is configured to screen out at least one outbound call sensitive waybill information from the waybill information set according to the obtained outbound customer complaint information set and the non-outbound customer complaint information set.

[0099] In some optional implementations of some embodiments, the screening unit 403 can be further configured to: for each waybill information in the waybill information set, determine the information difference between the outbound customer complaint information corresponding to the waybill information and the non-outbound customer complaint information corresponding to the waybill information as customer complaint sensitive information; screen out customer complaint sensitive information whose corresponding numerical values ​​are within the first predetermined number from the obtained customer complaint sensitive information set to obtain at least one customer complaint sensitive information; and determine at least one waybill information corresponding to the at least one customer complaint sensitive information as at least one outbound sensitive waybill information.

[0100] In some optional implementations of some embodiments, the screening unit 403 may be further configured to: for each waybill information in the waybill information set, determine the outbound customer complaint type information corresponding to the waybill information based on the outbound customer complaint information and non-outbound customer complaint information corresponding to the waybill information; and screen out at least one waybill information whose corresponding outbound customer complaint type information is the target outbound customer complaint type information from the waybill information set as at least one outbound sensitive waybill information.

[0101] In some optional implementations of some embodiments, the device 400 further includes: a sending unit (not shown in the figure). The sending unit may be configured to: send a target waybill operation request for the at least one outbound call sensitive waybill information to the target delivery terminal, so that a person corresponding to the target delivery terminal and a user corresponding to the at least one outbound call sensitive waybill information can perform an outbound call control operation.

[0102] In some optional implementations of some embodiments, the device 400 further includes: a step execution unit and a processing execution step (not shown in the figure). The step execution unit may be configured to: for each outbound call sensitive waybill information in the at least one outbound call sensitive waybill information, perform the following determination steps: determine the object complaint information of the waybill object corresponding to the outbound call sensitive waybill information; in response to determining that the object complaint information indicates that the waybill object has a historical complaint behavior, obtain the historical complaint event information corresponding to the waybill object; generate waybill communication method information according to the historical complaint event information; in response to determining that the object complaint information indicates that the waybill object does not have a historical complaint behavior, determine the outbound call sensitive waybill feature data corresponding to the outbound call sensitive waybill information; input the outbound call sensitive waybill feature data into the outbound call communication information generation model to generate outbound call communication information; determine the waybill communication method information according to the outbound call communication information. The processing execution step may be configured to: perform waybill communication processing for the at least one outbound call sensitive waybill information according to the obtained at least one waybill communication method information.

[0103] In some optional implementations of some embodiments, the outbound customer complaint information generation model and the non-outbound customer complaint information generation model are trained by the following steps: obtaining an outbound waybill information set and a non-outbound waybill information set; extracting the outbound waybill feature data corresponding to each outbound waybill information in the outbound waybill information set to obtain an outbound waybill feature data set, and extracting the non-outbound waybill feature data corresponding to each non-outbound waybill data in the non-outbound waybill information set to obtain a non-outbound waybill feature data set; performing model training on the initial outbound customer complaint information generation model based on the outbound waybill feature data set to obtain an outbound customer complaint information generation model; performing model training on the initial non-outbound customer complaint information generation model based on the non-outbound waybill feature data set to obtain a non-outbound customer complaint information generation model.

[0104] It can be understood that the units recorded in the outbound call sensitive waybill generating device 400 are similar to those in the reference Figure 2 Therefore, the operations, features and beneficial effects described above for the method are also applicable to the outbound call sensitive waybill generating device 400 and the units contained therein, and will not be described in detail here.

[0105] Reference below Figure 5 , which shows an electronic device (eg, Figure 1 Schematic diagram of the structure of the electronic device 101)500. Figure 5 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 disclosure.

[0106] like Figure 5 As shown, the electronic device 500 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory 502 or a program loaded from a storage device 508 to a random access memory 503. Various programs and data required for the operation of the electronic device 500 are also stored in the random access memory 503. The processing device 501, the read-only memory 502, and the random access memory 503 are connected to each other via a bus 504. An input / output interface 505 is also connected to the bus 504.

[0107] Typically, the following devices may be connected to the input / output interface 505: an input device 506 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 5 The electronic device 500 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 5 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0108] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 509, or installed from the storage device 508, or installed from the read-only memory 502. When the computer program is executed by the processing device 501, the above-mentioned functions defined in the method of some embodiments of the present disclosure are executed.

[0109] It should be noted that the computer-readable medium in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may 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 may 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 or 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 some embodiments of the present disclosure, the computer-readable storage medium may 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 some embodiments of the present disclosure, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0110] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0111] The computer-readable medium may be included in the electronic device; or it may exist independently without being installed in the electronic device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: obtains a waybill information set; for each waybill information in the waybill information set, performs the following generation steps: extracts the waybill feature data corresponding to the waybill information; inputs the waybill feature data into a pre-trained outbound customer complaint information generation model to generate outbound customer complaint information; inputs the waybill feature data into a pre-trained non-outbound customer complaint information generation model to generate non-outbound customer complaint information; based on the obtained outbound customer complaint information set and non-outbound customer complaint information set, at least one outbound sensitive waybill information is screened out from the waybill information set.

[0112] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0113] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square 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 square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0114] The units described in some embodiments of the present disclosure may be implemented by software or by hardware. The described units may also be provided in a processor, for example, may be described as: a processor including an acquisition unit, an execution unit, and a screening unit. The names of these units do not, in some cases, constitute limitations on the units themselves, for example, the acquisition unit may also be described as a "unit for acquiring a waybill information set".

[0115] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0116] Some embodiments of the present disclosure further provide a computer program product, including a computer program, which implements any of the above-mentioned methods for generating outbound call-sensitive waybills when executed by a processor.

[0117] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with the technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to) and the technical solutions formed.

Claims

1. A method for generating an outbound call sensitive waybill, comprising: Get the waybill information set; For each waybill information in the waybill information set, the following generation steps are performed: Extracting waybill characteristic data corresponding to the waybill information; Inputting the waybill feature data into a pre-trained outbound customer complaint information generation model to generate outbound customer complaint information; Inputting the waybill feature data into a pre-trained model for generating uncalled customer complaints to generate uncalled customer complaints information; At least one outbound call sensitive waybill information is screened out from the waybill information set according to the obtained outbound customer complaint information set and the non-outbound customer complaint information set.

2. The method according to claim 1, wherein: The step of screening out at least one outbound call sensitive waybill information from the waybill information set according to the obtained outbound customer complaint information set and the non-outbound customer complaint information set includes: For each waybill information in the waybill information set, determining the information difference between the outbound customer complaint information corresponding to the waybill information and the non-outbound customer complaint information corresponding to the waybill information as customer complaint sensitive information; Filter out sensitive customer complaint information whose corresponding values ​​are in the first predetermined number from the obtained set of sensitive customer complaint information to obtain at least one sensitive customer complaint information; The at least one waybill information corresponding to the at least one customer complaint sensitive information is determined as at least one outbound call sensitive waybill information.

3. The method according to claim 1, wherein: The step of screening out at least one outbound call sensitive waybill information from the waybill information set according to the obtained outbound customer complaint information set and the non-outbound customer complaint information set includes: For each waybill information in the waybill information set, determining the outbound customer complaint type information corresponding to the waybill information according to the outbound customer complaint information and the non-outbound customer complaint information corresponding to the waybill information; At least one waybill information corresponding to the outbound customer complaint type information as the target outbound customer complaint type information is screened out from the waybill information set as at least one outbound sensitive waybill information.

4. The method according to claim 1, wherein: The method further comprises: A target waybill operation request for the at least one outbound call sensitive waybill information is sent to the target delivery terminal, so that the personnel corresponding to the target delivery terminal and the user corresponding to the at least one outbound call sensitive waybill information can perform outbound call control operations.

5. The method according to claim 1, wherein: The method further comprises: For each outbound call sensitive waybill information in the at least one outbound call sensitive waybill information, the following determination steps are performed: Determine the object complaint information of the waybill object corresponding to the outbound call sensitive waybill information; In response to determining that the object complaint information indicates that the waybill object has a historical complaint behavior, obtaining historical complaint event information corresponding to the waybill object; Generate waybill communication method information based on the historical complaint event information; In response to determining that the object complaint information indicates that the waybill object has no historical complaint behavior, determining outbound call sensitive waybill feature data corresponding to the outbound call sensitive waybill information; Inputting the outbound call sensitive waybill feature data into an outbound call communication information generation model to generate outbound call communication information; Determine the waybill communication method information according to the outbound call communication information; According to the obtained at least one waybill communication mode information, a waybill communication process is performed for the at least one outbound call sensitive waybill information.

6. The method according to claim 1, wherein: The outbound customer complaint information generation model and the non-outbound customer complaint information generation model are trained by the following steps: Get the outbound waybill information set and the non-outbound waybill information set; Extracting outbound waybill feature data corresponding to each outbound waybill information in the outbound waybill information set to obtain an outbound waybill feature data set, and extracting non-outbound waybill feature data corresponding to each non-outbound waybill data in the non-outbound waybill information set to obtain a non-outbound waybill feature data set; According to the outbound waybill feature data set, the initial outbound customer complaint information generation model is trained to obtain the outbound customer complaint information generation model; According to the feature data set of the uncalled waybills, the initial uncalled customer complaint information generation model is trained to obtain the uncalled customer complaint information generation model.

7. An outbound call sensitive waybill generation device, comprising: An acquisition unit, configured to acquire a waybill information set; The execution unit is configured to execute the following generation steps for each waybill information in the waybill information set: extracting waybill feature data corresponding to the waybill information; Inputting the waybill feature data into a pre-trained outbound customer complaint information generation model to generate outbound customer complaint information; Inputting the waybill feature data into a pre-trained model for generating uncalled customer complaints to generate uncalled customer complaints information; The screening unit is configured to screen out at least one outbound call sensitive waybill information from the waybill information set according to the obtained outbound customer complaint information set and the non-outbound customer complaint information set.

8. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer readable medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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