Method and device for evaluating sales behavior based on block chain, medium and electronic equipment

An evaluation method and blockchain technology, applied in the blockchain field, can solve problems such as the timeliness of consuming human resources, and achieve the effect of promoting effective promotion and ensuring safe sharing.

Active Publication Date: 2019-03-15
TAIKANG LIFE INSURANCE CO LTD
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AI-Extracted Technical Summary

Problems solved by technology

[0005] The purpose of this disclosure is to provide a method for evaluating sales behavior based on blockchain, a device for evaluating sales behavior based on blockchain, storage media, and electron...
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Method used

[0051] The present disclosure stores the sales behavior information in the blockchain network, so that the sales behavior information can be guaranteed to be tamper-proof through the blockchain network, and the traceable processing of the sales behavior information can be realized based on the storage of the blockchain network , which in turn can effectively ensure the safe sharing of sales behavior information.
[0078] The data format definition subsystem 220 can store the information involved in the present disclosure according to a predefined data structure, so as to ensure high efficiency of information storage and information processing. Wherein, the input may be sales behavior information, for example, information such as audio and video of product promotion by salespersons to customers, and follow-up feedback from customers. In addition, the input information may also include information such as relevant pictures or videos, public keys and signatures of relevant personnel that are helpful to further confirm relevant sales integrity tracking and management activities. The output can be the storage link of relevant voucher materials for sales misleading tracking management information, the system automatically identifies possible risks of sales misleading a...
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Abstract

The invention discloses a sales behavior evaluation method and a device based on a block chain, a medium and an electronic device, which relate to the technical field of the block chain. The sales behavior evaluation method based on the block chain comprises the following steps: storing a plurality of sales behavior information through the block chain network; Determining a sales behavior evaluation result corresponding to each of the sales behavior information, and determining sales misleading information based on the plurality of sales behavior information; Training a machine learning modelusing the sales misleading information and a sales behavior evaluation result corresponding to each of the sales behavior information; If it is detected that new sales behavior information is input into the block chain network, the new sales behavior information is input into the trained machine learning model to determine a sales behavior evaluation result corresponding to the new sales behaviorinformation. The present disclosure may evaluate the sales behavior of a salesperson to determine whether there is a lack of integrity on the part of the salesperson in the sales process.

Application Domain

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Technology Topic

Chain networkBlockchain +3

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  • Method and device for evaluating sales behavior based on block chain, medium and electronic equipment
  • Method and device for evaluating sales behavior based on block chain, medium and electronic equipment
  • Method and device for evaluating sales behavior based on block chain, medium and electronic equipment

Examples

  • Experimental program(1)

Example Embodiment

[0039] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms, and should not be construed as being limited to the examples set forth herein; on the contrary, the provision of these embodiments makes the present disclosure more comprehensive and complete, and fully conveys the concept of the example embodiments To those skilled in the art. The described features, structures or characteristics can be combined in one or more embodiments in any suitable way. In the following description, many specific details are provided to give a sufficient understanding of the embodiments of the present disclosure. However, those skilled in the art will realize that the technical solutions of the present disclosure can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be used. In other cases, the well-known technical solutions are not shown or described in detail to avoid overwhelming the crowd and obscure all aspects of the present disclosure.
[0040] In addition, the drawings are only schematic illustrations of the present disclosure, and are not necessarily drawn to scale. The same reference numerals in the figures indicate the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in the form of software, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and/or processor devices and/or microcontroller devices.
[0041] The flowchart shown in the drawings is only an exemplary description, and does not necessarily include all steps. For example, some steps can be decomposed, and some steps can be combined or partially combined, so the actual execution order may be changed according to actual conditions.
[0042] The block chain-based sales behavior evaluation method described below can be implemented based on a server. In this case, the sales behavior evaluation device of the present disclosure can be configured in the server. However, the sales behavior evaluation method of the present disclosure can also be implemented by a terminal device, which is not particularly limited in this exemplary embodiment.
[0043] figure 1 It schematically shows a flowchart of a blockchain-based sales behavior evaluation method according to an exemplary embodiment of the present disclosure. reference figure 1 The method for evaluating sales behavior based on blockchain may include the following steps:
[0044] S12. Store multiple sales behavior information through the blockchain network.
[0045] In an exemplary embodiment of the present disclosure, the sales behavior information may be information generated by sales personnel performing sales activities for customers. Specifically, the sales behavior information may include audio, video, and customer feedback information of the salesperson's product promotion to the customer. For example, when a salesperson sells a product to a customer, he can record the conversation between the salesperson and the customer through recording devices such as mobile phones and voice recorders. Among them, the customer's conversation can be determined from the conversation between the salesperson and the customer. Feedback information, such as the degree of interest in the product, opinions on the product or sales, etc. In addition, in the case of telephone sales between sales staff and customers, audio files can be generated directly based on the content of the call.
[0046] After the server obtains the audio file or video file, it can send the audio file or video file in the form of blocks to each node of the blockchain network.
[0047] In addition, after the server obtains the audio file or video file, it can perform voice recognition and semantic analysis through the audio file or video file, so as to use the analyzed data as the sales behavior information described in the present disclosure. For example, a trained convolutional neural network may be used to recognize audio to determine text information corresponding to the audio, and the recognized text information is used as the sales behavior information of the present disclosure. It is easy to understand that other voice recognition technologies can also be used to determine the text information corresponding to the audio at the time of sale. These technologies can include hidden Markov methods, vector quantization methods, etc., which are not special in this exemplary embodiment. limited.
[0048] After the audio file or video file is recognized through voice recognition technology, the server can send the recognized text information to each node of the blockchain.
[0049] It should be understood that the sales behavior information may also include paper reports or electronic reports generated by sales staff after product promotion to customers. In the case of paper reports, electronically scan the paper reports confirmed by the customer, and identify the content through OCR (Optical Character Recognition) technology, and use the recognized results as sales behavior information; In the case of electronic reports, electronic reports generated by, for example, tablets can be directly used as sales behavior information.
[0050] In addition, the present disclosure can also upload relevant pictures or videos that are helpful for evaluating sales behaviors to the blockchain network.
[0051] By storing the sales behavior information in the blockchain network, the present disclosure can ensure that the sales behavior information cannot be tampered with through the blockchain network, and can realize the traceability processing of the sales behavior information based on the storage of the blockchain network. Effectively ensure the safe sharing of sales behavior information.
[0052] S14. Determine a sales behavior evaluation result corresponding to each of the sales behavior information, and determine sales misleading information based on the plurality of sales behavior information.
[0053] In the exemplary embodiment of the present disclosure, each sales behavior information stored in the blockchain network can be evaluated to determine the sales behavior evaluation result for the sales behavior information. Specifically, these sales behavior information can be evaluated artificially, and during the evaluation process, the evaluation can be based on the actually promoted information contained in the sales behavior information and customer feedback information. For example, you can configure corresponding weights for the information actually promoted and customer feedback information, and determine the sales behavior evaluation results corresponding to each sales behavior information based on the weights and combined with human analysis.
[0054] In addition, the sales misleading information can be determined based on the sales behavior information, where the sales misleading information can be understood as information that affects the evaluation of the sales behavior. For example, for the scenario of insurance sales, through human analysis, it can be determined that the types of misleading sales information include false publicity, one-sided introduction, exaggerated functions, confusing products, and tampering with customer information. However, the types of sales misleading information may include other classifications based on different sales scenarios, which are not specifically limited in this exemplary embodiment.
[0055] It should be understood that for a piece of sales behavior information stored in the blockchain network, it may not contain misleading sales information. In this case, it can be considered that the sales promotion behavior of the corresponding salesperson is completely honest. In addition, for another sales behavior information, it may contain multiple types of sales misleading information. In this case, it can be considered that the corresponding salesperson has fraudulent behavior in the promotion of sales.
[0056] S16. Use the sales misleading information and the sales behavior evaluation results corresponding to each of the sales behavior information to train a machine learning model.
[0057] In the exemplary embodiment of the present disclosure, first, the misleading information corresponding to each sales behavior information stored in the blockchain network can be determined. Wherein, if a piece of sales behavior information has no sales misleading information, then the sales misleading information corresponding to the sales behavior information is recorded as empty.
[0058] Next, the sales misleading information corresponding to each sales behavior information can be used as the input of the machine learning model, and the determined sales behavior evaluation results corresponding to the sales misleading information can be used as the output of the machine learning model to train the machine learning model . It should be understood that the process of training the machine learning model is the process of determining the parameters of the machine learning model.
[0059] According to some embodiments of the present disclosure, the machine learning model described in the present disclosure may be configured as a Gaussian mixture model. When the types of misleading sales information include five types: false promotion, one-sided introduction, exaggerated features, confusing products, and tampering with customer information, the following formula 1 can be used to describe the Gaussian mixture model:
[0060] Risk(x)=p(x|θ)=sum(p(x|θj)*wj), j=1,2,3,4,5 (Formula 1)
[0061] Among them, Risk represents the risk of misleading sales in sales behavior, x represents a sales behavior information stored in the blockchain network, θj represents the jth type of misleading sales information, and wj is the weight of the jth type of sales misleading information type.
[0062] Based on the determined sales misleading information and the sales behavior evaluation results corresponding to each sales behavior information as training samples, the Gaussian mixture model described by formula 1 is trained to determine the trained Gaussian mixture model.
[0063] In addition, the present disclosure may also use other machine learning models to replace the above-mentioned Gaussian mixture model. For example, a multilayer neural network may be used as the machine learning model of the present disclosure. There is no particular limitation on this in this exemplary embodiment.
[0064] S18. If it is detected that new sales behavior information is entered in the blockchain network, input the new sales behavior information into the trained machine learning model to determine the sales behavior corresponding to the new sales behavior information Evaluation results.
[0065] After the salesperson completes the promotion of the product to the customer, the generated new sales behavior information can be entered into the blockchain network. Specifically, new sales behavior information can be entered into the blockchain network via the aforementioned server. However, the new sales behavior information can also be entered into the blockchain network through other terminal devices, which can be computers deployed in sales outlets, mobile phones of sales personnel, and so on.
[0066] Similarly, the salesperson may generate an audio file after propagating. In this case, the server can perform voice recognition on the audio file to determine new sales behavior information.
[0067] Next, the new sales behavior information can be input into the trained machine learning model to determine the sales behavior evaluation results corresponding to the new sales behavior information, that is, it can be determined that the salesperson is at risk of misleading sales.
[0068] Still taking the Gaussian mixture model as a machine learning model as an example, if the new sales behavior information is recorded as y, the corresponding risk (y) of the salesperson's misleading sales can be expressed as the following formula 2:
[0069] Risk(y)=p(y|θ)=sum(p(y|θj)*wj), j=1,2,3,4,5 (Formula 2)
[0070] However, other machine learning models can also be used to determine the risk value of misleading sales by the salesperson, which is not specifically limited in this exemplary embodiment.
[0071] According to some embodiments of the present disclosure, after determining the sales behavior evaluation result corresponding to the new sales behavior, the server can also determine whether the risk value corresponding to the new sales behavior information is greater than a preset threshold. Among them, the preset threshold can be set by business managers based on actual sales. If it is determined that the risk value corresponding to the new sales behavior information is greater than the preset threshold, it means that the salesperson has a serious problem of lack of integrity. In this case, the server can send an alarm message to the salesperson to restrict the sales Sales behavior of personnel.
[0072] According to other embodiments of the present disclosure, the performance of sales personnel can also be evaluated based on the sales behavior evaluation method of the present disclosure. Specifically, the sales behavior evaluation result of the target salesperson within a preset time period (for example, one month) can be determined, and the performance of the target salesperson can be evaluated according to the sales behavior evaluation result within the preset time period.
[0073] For example, Zhang San had 8 sales behaviors in a month, and 6 of them had sales misleading behaviors. In this case, Zhang San's performance appraisal results were poor. In addition, Zhang San's salary can also be determined according to the assessment results.
[0074] It should be noted that although the various steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that these steps must be performed in the specific order, or that all the steps shown must be performed to achieve the desired the result of. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step for execution, and/or one step may be decomposed into multiple steps for execution, etc.
[0075] The following will refer to figure 2 A blockchain-based sales behavior evaluation system according to an exemplary embodiment of the present disclosure will be described.
[0076] reference figure 2 , The blockchain-based sales behavior evaluation system of the exemplary embodiment of the present disclosure may include a blockchain network construction subsystem 210, a data format definition subsystem 220, a sales behavior information storage subsystem 230, and a sales behavior evaluation subsystem 240 And the system performance evaluation subsystem 250.
[0077] Specifically, the blockchain network construction subsystem 210 is used for the construction, update, and maintenance mechanism of blockchain nodes and the construction, update, and maintenance of the blockchain network. For example, the basic business organization of an insurance company can be used as the smallest node, and a blockchain network can be constructed based on the participation of one or more insurance groups/companies.
[0078] The data format definition subsystem 220 can store the information involved in the present disclosure according to a pre-defined data structure to ensure high efficiency of information storage and information processing. Among them, the input may be sales behavior information, for example, audio, video, and follow-up feedback of the customer for product promotion by the salesperson. In addition, the input information can also include information such as relevant pictures or videos that help to further confirm the relevant sales integrity tracking management activities, and the public keys and signatures of relevant personnel. The output can be the storage link of relevant voucher materials for sales misleading tracking management information, the system automatically recognizes the possible risk of misleading sales and sends reminders to relevant departments, the public key (account address) of the relevant information visitor, etc.
[0079] Specifically, the predefined data structure can be as shown in Table 1:
[0080] Table 1
[0081]
[0082] In the data structure shown in Table 1, because the sales behavior information materials and other materials usually contain some large amounts of information such as images and documents, in order to improve storage efficiency and solve the problem of excessive block information, the In the embodiment of the invention, relatively large materials such as images can be stored in the block in the form of a link. The value of this link is the hash value obtained by encrypting the material through a hash function, such as SHA1. The way the hash function gets the pointer link can ensure that the content cannot be tampered with. The actual materials can be stored in the local storage device of the blockchain node, or in the form of cloud storage. At the same time, in order to ensure the high reliability of material storage, redundant coding can be used to store the materials, such as RS coding (ie Reed-Solomon codes, which is a forward error correction channel coding, which is corrected by oversampling The data generated by the polynomial is valid) or LDPC (Low Density Parity CheckCode, low-density parity check code) encoding methods, etc., perform redundant encoding processing on the material.
[0083] The sales behavior information storage subsystem 230 is used to store sales behavior information. Specifically, each sales behavior information can be uploaded to the blockchain network in the format of Table 1 above, so that the sales behavior information storage subsystem 230 can store it.
[0084] The sales behavior evaluation subsystem 240 can use the above-mentioned sales behavior evaluation method to evaluate the sales behavior, which will not be repeated here.
[0085] The system performance evaluation subsystem 250 can be used to evaluate the above sales behavior evaluation methods, and then evaluate the timeliness, effectiveness and accuracy of sales integrity tracking management, in order to effectively implement sales integrity tracking management in the blockchain network, thereby effectively promoting The effective promotion of the application of blockchain technology in sales integrity tracking management.
[0086] Further, this example embodiment also provides a block chain-based sales behavior evaluation device.
[0087] image 3 It schematically shows a block diagram of a block chain-based sales behavior evaluation device according to an exemplary embodiment of the present disclosure. reference image 3 The block chain-based sales behavior evaluation device 3 according to the exemplary embodiment of the present disclosure may include an information storage module 31, a sample determination module 33, a model training module 35, and a sales behavior evaluation module 37.
[0088] Specifically, the information storage module 31 may be used to store a plurality of sales behavior information through a blockchain network; the sample determination module 33 may be used to determine the sales behavior evaluation results corresponding to each of the sales behavior information, and based on the plurality of sales behavior information Sales behavior information determines sales misleading information; the model training module 35 can be used to use the sales misleading information and the sales behavior evaluation results corresponding to each of the sales behavior information to train a machine learning model; the sales behavior evaluation module 37 can use If it is detected that new sales behavior information is entered in the blockchain network, then the new sales behavior information is input into the trained machine learning model to determine the sales behavior evaluation corresponding to the new sales behavior information result.
[0089] According to the block chain-based sales behavior evaluation device of the exemplary embodiment of the present disclosure, on the one hand, based on the solution of the present disclosure, combined with the related technology of machine learning, the sales behavior of sales personnel can be effectively evaluated, avoiding manual work. Confirming the integrity of the salesperson leads to the consumption of human resources and poor timeliness; on the other hand, the present disclosure stores sales behavior information in the blockchain network, so that the blockchain network can ensure that the sales behavior information cannot be tampered with. And it can realize the traceability processing of sales behavior information based on the storage of the blockchain network, thereby effectively ensuring the safe sharing of sales behavior information; on the other hand, the present disclosure can be determined based on the sales behavior information stored in the blockchain network Whether the sales behavior of sales staff is honest or not will help promote the effective promotion of the application of blockchain technology in the tracking and management of sales integrity.
[0090] According to an exemplary embodiment of the present disclosure, the model training module is configured to: determine the sales misleading information corresponding to each of the sales behavior information; use the sales misleading information corresponding to each of the sales behavior information as the input of the machine learning model, and The sales behavior evaluation result corresponding to the sales misleading information is used as an output, and the machine learning model is trained.
[0091] According to an exemplary embodiment of the present disclosure, the machine learning model is configured as a Gaussian mixture model.
[0092] According to an exemplary embodiment of the present disclosure, refer to Figure 4 Compared with the sales behavior evaluation device 3 based on the blockchain, the sales behavior evaluation device 4 based on the blockchain may further include a voice data acquisition module 41 and a voice recognition module 43.
[0093] Specifically, the voice data acquisition module 41 may be used to acquire new sales voice data; the voice recognition module 43 may be used to perform voice recognition on the new sales voice data to determine the new sales behavior information.
[0094] According to an exemplary embodiment of the present disclosure, the sales behavior information includes customer feedback information; wherein, reference Figure 5 The sample determination module 35 includes an evaluation result determination unit 501.
[0095] Specifically, the evaluation result determining unit 501 may be configured to determine a sales behavior evaluation result corresponding to each of the sales behavior information based on customer feedback information corresponding to each of the sales behavior information.
[0096] According to an exemplary embodiment of the present disclosure, the evaluation result of the sales behavior is the risk value of misleading sales; wherein, reference Image 6 Compared with the sales behavior evaluation device 3 based on the blockchain, the block chain-based sales behavior evaluation device 6 may further include a risk value judgment module 61 and an alarm sending module 63.
[0097] Specifically, the risk value judgment module 61 can be used to judge whether the risk value of misleading sales corresponding to the new sales behavior information is greater than a preset threshold; the alarm sending module 63 can be used to determine whether the new sales behavior information corresponds to If the risk value of misleading sales is greater than the preset threshold, an alarm message is sent to the salesperson corresponding to the new sales behavior information.
[0098] According to an exemplary embodiment of the present disclosure, refer to Figure 7 Compared with the sales behavior evaluation device 3 based on the blockchain, the block chain-based sales behavior evaluation device 7 may further include a performance evaluation module 71.
[0099] Specifically, the performance appraisal module 71 can be used to determine the sales behavior evaluation results of the target salesperson within a preset time period, and perform evaluation on the target salesperson’s performance according to the sales behavior evaluation results within the preset time period. Assessment.
[0100] In addition, it is easy to understand that the performance evaluation module 71 may also be included in the sales behavior evaluation device 6 based on the blockchain.
[0101] Since the various functional modules of the program running performance analysis device of the embodiment of the present invention are the same as those in the foregoing method of the invention, they will not be repeated here.
[0102] In the exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium on which is stored a program product capable of implementing the above method in this specification. In some possible implementation manners, various aspects of the present invention may also be implemented in the form of a program product, which includes program code, and when the program product runs on a terminal device, the program code is used to make the The terminal device executes the steps according to various exemplary embodiments of the present invention described in the above "Exemplary Method" section of this specification.
[0103] reference Picture 8 As shown, a program product 800 for implementing the above method according to an embodiment of the present invention is described. It can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be installed in a terminal device, such as a personal computer. Run on. However, the program product of the present invention is not limited thereto. In this document, the readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, device, or device.
[0104] The program product can use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or a combination of any of the above. More specific examples (non-exhaustive list) of readable storage media include: electrical connections with one or more wires, portable disks, hard disks, random access memory (RAM), read only memory (ROM), erasable Type programmable read only memory (EPROM or flash memory), optical fiber, portable compact disk read only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
[0105] The computer-readable signal medium may include a data signal propagated in baseband or as a part of a carrier wave, and readable program code is carried therein. This propagated data signal can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. The readable signal medium may also be any readable medium other than a readable storage medium, and the readable medium may send, propagate, or transmit a program for use by or in combination with the instruction execution system, apparatus, or device.
[0106] The program code contained on the readable medium can be transmitted by any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.
[0107] The program code used to perform the operations of the present invention can be written in any combination of one or more programming languages. The programming languages ​​include object-oriented programming languages—such as Java, C++, etc., as well as conventional procedural Programming language-such as "C" language or similar programming language. The program code can be executed entirely on the user's computing device, partly on the user's device, executed as an independent software package, partly on the user's computing device and partly executed on the remote computing device, or entirely on the remote computing device or server Executed on. In the case of a remote computing device, the remote computing device can be connected to a user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using Internet service providers) Business to connect via the Internet).
[0108] In an exemplary embodiment of the present disclosure, there is also provided an electronic device capable of implementing the above method.
[0109] Those skilled in the art can understand that various aspects of the present invention can be implemented as a system, a method, or a program product. Therefore, various aspects of the present invention can be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which can be collectively referred to herein as "Circuit", "Module" or "System".
[0110] Refer below Picture 9 The electronic device 900 according to this embodiment of the present invention will be described. Picture 9 The displayed electronic device 900 is only an example, and should not bring any limitation to the function and application scope of the embodiment of the present invention.
[0111] Such as Picture 9 As shown, the electronic device 900 is in the form of a general-purpose computing device. The components of the electronic device 900 may include, but are not limited to: the aforementioned at least one processing unit 910, the aforementioned at least one storage unit 920, a bus 930 connecting different system components (including the storage unit 920 and the processing unit 910), and a display unit 940.
[0112] Wherein, the storage unit stores program code, and the program code can be executed by the processing unit 910, so that the processing unit 910 executes the various exemplary methods described in the "Exemplary Method" section of this specification. Implementation steps. For example, the processing unit 910 may execute figure 1 Step S12 shown in the following: Store a plurality of sales behavior information through the blockchain network; Step S14: Determine the sales behavior evaluation result corresponding to each of the sales behavior information, and determine the sales misleading information based on the plurality of sales behavior information Step S16: Use the sales misleading information and the sales behavior evaluation results corresponding to each of the sales behavior information to train a machine learning model; Step S18: If a new sales behavior is detected in the blockchain network Information, the new sales behavior information is input into the trained machine learning model to determine the sales behavior evaluation result corresponding to the new sales behavior information.
[0113] The storage unit 920 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 9201 and/or a cache storage unit 9202, and may further include a read-only storage unit (ROM) 9203.
[0114] The storage unit 920 may also include a program/utility tool 9204 having a set of (at least one) program module 9205. Such program module 9205 includes but is not limited to: an operating system, one or more application programs, other program modules, and program data, Each of these examples or some combination may include the implementation of a network environment.
[0115] The bus 930 may represent one or more of several types of bus structures, including a storage unit bus or a storage unit controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local area using any bus structure among multiple bus structures. bus.
[0116] The electronic device 900 may also communicate with one or more external devices 1000 (such as keyboards, pointing devices, Bluetooth devices, etc.), and may also communicate with one or more devices that enable a user to interact with the electronic device 900, and/or communicate with Any device (such as a router, modem, etc.) that enables the electronic device 900 to communicate with one or more other computing devices. This communication can be performed through an input/output (I/O) interface 950. In addition, the electronic device 900 may also communicate with one or more networks (for example, a local area network (LAN), a wide area network (WAN), and/or a public network, such as the Internet) through the network adapter 960. As shown in the figure, the network adapter 960 communicates with other modules of the electronic device 900 through the bus 930. It should be understood that although not shown in the figure, other hardware and/or software modules can be used in conjunction with the electronic device 900, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives And data backup storage system, etc.
[0117] Through the description of the foregoing embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein can be implemented by software, or can be implemented by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (can be a CD-ROM, U disk, mobile hard disk, etc.) or on the network , Including several instructions to make a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) execute the method according to the embodiment of the present disclosure.
[0118] In addition, the above-mentioned drawings are merely schematic illustrations of the processing included in the method according to the exemplary embodiment of the present invention, and are not intended for limitation. It is easy to understand that the processing shown in the above drawings does not indicate or limit the time sequence of these processings. In addition, it is easy to understand that these processes can be executed synchronously or asynchronously in multiple modules, for example.
[0119] It should be noted that although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above may be embodied in one module or unit. Conversely, the features and functions of a module or unit described above can be further divided into multiple modules or units to be embodied.
[0120] Those skilled in the art will easily think of other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptive changes of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or conventional technical means in the technical field not disclosed in the present disclosure . The description and embodiments are only regarded as exemplary, and the true scope and spirit of the present disclosure are pointed out by the claims.
[0121] It should be understood that the present disclosure is not limited to the precise structure that has been described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present disclosure is only limited by the appended claims.

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