Financial service data utilization method and system oriented to government affair service scene

Abstract

The invention relates to the technical field of financial services, in particular to a government affair service scene-oriented financial service data utilization method and system, which can increase the transparency of government affair and financial services, reduce information asymmetry and establish and enhance the sense of trust of users to the government and financial institutions. The method comprises the steps of collecting government affair data and financial data related to enterprises and individuals from functional departments and financial institutions of a government; constructing a user portrait based on government affair data and financial data of enterprises and individuals; inputting the user portrait into a pre-constructed user behavior analysis model, analyzing a user behavior mode, and obtaining demand hotspots of government affair service and financial service; generating a government affair service strategy and a financial service strategy according to the user portrait and the demand hotspot; and fusing the government affair service strategy and the financial service strategy to obtain a financial service strategy, and pushing the financial service strategy to a user platform.

Description

Technical Field

[0001] The present invention relates to the technical field of financial services, and particularly to a method and system for utilizing financial service data in the context of government services. Background Art

[0002] Traditional government services and financial service models often operate independently, leading to a serious information silo phenomenon, unable to fully exploit data value, and also unable to provide personalized and efficient one-stop solutions. When enterprises and individuals handle government service matters, they often have to run back and forth between multiple institutions. At the same time, when seeking financial services, they also face problems such as information asymmetry and long approval processes.

[0003] In the current era of digital transformation, data sharing and integration between the government and financial institutions have become key factors in improving the efficiency and quality of government services. With the development of advanced technologies such as big data and artificial intelligence, how to effectively utilize cross-departmental data resources, especially in the context of government services, to accurately meet the diverse needs of enterprises and individuals has become an urgent problem to be solved. Summary of the Invention

[0004] To solve the above technical problems, the present invention provides a method for utilizing financial service data in the context of government services, which can increase the transparency of government and financial services, reduce information asymmetry, and establish and strengthen users' trust in the government and financial institutions.

[0005] In a first aspect, the present invention provides a method for utilizing financial service data in the context of government services, the method comprising:

[0006] Collecting government data and financial data related to enterprises and individuals from various government functional departments and financial institutions;

[0007] Constructing a user profile based on the government data and financial data of enterprises and individuals;

[0008] Inputting the user profile into a pre-constructed user behavior analysis model to analyze the user behavior pattern and obtain the demand hotspots for government services and financial services;

[0009] Generating government service strategies and financial service strategies according to the user profile and demand hotspots;

[0010] Fusing the government service strategy and the financial service strategy to obtain a financial service strategy, and pushing the financial service strategy to the user platform.

[0011] Further, the government data includes basic information data, administrative management data, and economic operation data.

[0012] Further, the financial data includes transaction data, credit data, market data, and user behavior data.

[0013] Further, the method for constructing a user portrait includes:

[0014] Clean and preprocess the collected government affairs data and financial data, including removing duplicate data, handling missing values, and performing data standardization;

[0015] On the basis of data integration, identify and associate the same user in different data sources;

[0016] Extract key features from the integrated data; the extracted features include the user's basic information, economic activities, and financial behaviors;

[0017] Utilize machine learning and data mining techniques to establish a user portrait model to describe the characteristics and behavior patterns of different user groups.

[0018] Further, the method for constructing the user behavior analysis model includes:

[0019] Collect the government affairs data and financial data of users, clean the collected data, handle missing values and outliers, and perform data type conversion; merge the data from different sources to eliminate redundancy;

[0020] Select a deep learning model as the basic architecture of the model, and the deep learning model includes logistic regression, random forest, support vector machine, and neural network;

[0021] Divide the data set into a training set, a validation set, and a test set; use the training set data to train the selected model; use the validation set to evaluate the generalization ability of the model;

[0022] Use the test set to evaluate the model performance, paying attention to indicators such as accuracy, precision, recall rate, F1 score, and root mean square error; according to the evaluation results, adjust the model structure and parameters;

[0023] Deploy the optimized model to the production environment to analyze user behavior data in real time.

[0024] Further, the method for generating government service strategies and financial service strategies includes:

[0025] Based on the user portrait and demand hotspots, analyze the characteristics of enterprises and individuals; including credit status, transaction habits, economic strength, preferred service types, and potential financial needs;

[0026] Utilize the user portrait to plan simplified government affair handling processes for enterprises and individuals with different needs;

[0027] Automatically match applicable government subsidies and tax exemption policies according to the characteristics of enterprises and individuals;

[0028] Recommend a financial product portfolio based on the user's risk tolerance, asset size, and historical transaction behavior factors using machine learning algorithms;

[0029] Provide a credit score for the user through data analysis and offer credit enhancement services based on the score results.

[0030] Furthermore, the method of pushing financial service strategies to the user platform includes user platform interface docking, personalized push strategies, data encryption, privacy protection, effect tracking, and feedback loops.

[0031] On the other hand, this application also provides a financial service data utilization system for the government service scenario. The system includes:

[0032] A data collection module that collects government affairs data and financial data related to enterprises and individuals from various government functional departments and financial institutions. The government affairs data includes basic information data, administrative management data, and economic operation data. The financial data includes transaction data, credit data, market data, and user behavior data;

[0033] A user portrait construction module that constructs a user portrait based on the government affairs data and financial data of enterprises and individuals;

[0034] A behavior analysis model module that inputs the user portrait into a pre-constructed user behavior analysis model to analyze the user behavior pattern and obtain the demand hotspots for government service and financial service;

[0035] A strategy generation module that generates government service strategies and financial service strategies based on the user portrait and demand hotspots;

[0036] A strategy integration and push module that integrates the government service strategies and financial service strategies to obtain financial service strategies and pushes the financial service strategies to the user platform.

[0037] In a third aspect, this application provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored on the memory and executable on the processor. The transceiver, the memory, and the processor are connected through the bus. When the computer program is executed by the processor, it implements the steps in any one of the above methods.

[0038] In a fourth aspect, this application also provides a computer-readable storage medium with a computer program stored thereon. When the computer program is executed by a processor, it implements the steps in any one of the above methods.

[0039] Compared with the prior art, the present invention has the following beneficial effects: the method collects data across departments, effectively breaks the phenomenon of information islands, and promotes the integration and sharing of government affairs and financial data; it not only improves the comprehensiveness of the data, but also provides a solid foundation for subsequent analysis and application, and helps to maximize the value of data;

[0040] The steps of building user portraits enable service strategies to more accurately match the characteristics and needs of enterprises and individuals; personalized service design can improve user experience, meet diversified needs, and enhance the pertinence and effectiveness of services;

[0041] Using user behavior analysis models to identify demand hotspots for government services and financial services, making strategy formulation closer to the real needs of the market and users, helping to quickly respond to changes, optimize resource allocation, and improve the foresight and flexibility of services;

[0042] Integrate government service strategies with financial service strategies and push them to the user platform in a unified manner, thus realizing a truly one-stop solution; greatly simplifying the process of handling affairs for enterprises and individuals, reducing time and costs, and improving overall service efficiency;

[0043] This method uses advanced technologies such as big data and artificial intelligence to promote innovation in the model of government services and financial services. Through continuous data analysis and strategy adjustment, it can continuously optimize service processes, introduce new service products, and adapt to the development requirements of the digital age.

[0044] In summary, this method effectively solves the problems of information islands, cumbersome processes, and single services in the traditional model through integrated data processing and intelligent analysis. It can increase the transparency of government affairs and financial services, reduce information asymmetry, and establish and strengthen users' trust in the government and financial institutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a flow chart of the present invention;

[0046] Figure 2 It is a structural diagram of a financial service data utilization system for government service scenarios. DETAILED DESCRIPTION

[0047] In the description of the present application, those skilled in the art should understand that the present application can be implemented as a method, an apparatus, an electronic device, and a computer-readable storage medium. Therefore, the present application can be specifically implemented in the following forms: complete hardware, complete software (including firmware, resident software, microcode, etc.), and a combination of hardware and software. In addition, in some embodiments, the present application can also be implemented in the form of a computer program product in one or more computer-readable storage media, which contain computer program code.

[0048] The above-mentioned computer-readable storage media can adopt any combination of one or more computer-readable storage media. Computer-readable storage media include: electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or components, or any combination of the above. More specific examples of computer-readable storage media include: portable computer disks, hard disks, random access memories, read-only memories, erasable programmable read-only memories, flash memories, optical fibers, compact disc read-only memories, optical storage devices, magnetic storage devices, or any combination of the above. In the present application, the computer-readable storage media can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, device, or component.

[0049] In the technical solution of the present application, the acquisition, storage, use, processing, etc. of data all comply with the relevant provisions of national laws.

[0050] The present application describes the provided method, apparatus, and electronic device through flowcharts and / or block diagrams.

[0051] It should be understood that each block of the flowchart and / or block diagram, as well as the combination of blocks in the flowchart and / or block diagram, can be implemented by computer-readable program instructions. These computer-readable program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, thereby producing a machine. These computer-readable program instructions are executed by a computer or other programmable data processing devices, resulting in an apparatus that implements the functions / operations specified in the blocks of the flowchart and / or block diagram.

[0052] These computer-readable program instructions can also be stored in a computer-readable storage medium that enables a computer or other programmable data processing device to work in a specific manner. In this way, the instructions stored in the computer-readable storage medium produce an instruction device product that includes the functions / operations specified in the blocks of the flowchart and / or block diagram.

[0053] Computer-readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other devices, so that a series of operation steps are performed on the computer, other programmable data processing apparatus, or other devices to generate a computer-implemented process, thereby enabling the instructions executed on the computer or other programmable data processing apparatus to provide a process for implementing the functions / operations specified in the blocks of the flowchart and / or block diagram.

[0054] The present application will be described below with reference to the accompanying drawings in the present application.

[0055] Embodiment 1: As Figure 1 shown, a method for utilizing financial service data for government service scenarios of the present invention specifically includes the following steps:

[0056] S1. Collect government data and financial data related to enterprises and individuals from various government functional departments and financial institutions; the government data includes basic information data, administrative management data, and economic operation data; the financial data includes transaction data, credit data, market data, and user behavior data;

[0057] Step S1 is the basis of the entire data utilization method, and its core lies in the collection and integration of cross-departmental data;

[0058] Clarify the specific sources of the required data, including industrial and commercial registration information and tax records from the government's industrial and commercial tax departments; bank transaction records and credit records from major commercial banks and credit institutions; as well as stock market, bond market data, and user behavior traces left by online banking, mobile payment, etc.;

[0059] Negotiate with government functional departments and financial institutions to establish a secure data interface to achieve automated data scraping and transmission; ensure that the data acquisition process complies with relevant laws and regulations on privacy protection and data security;

[0060] Implement data cleaning to eliminate incorrect, duplicate, incomplete, or inaccurate information; use data quality monitoring tools to regularly check data consistency and integrity to ensure data availability;

[0061] Perform desensitization processing on sensitive information involving personal privacy to ensure the use of data without disclosing personal information;

[0062] Adopt the SSL / TLS protocol to encrypt the data transmission process, and use encryption algorithms such as AES and RSA to encrypt and store sensitive data during storage to ensure the security of data in both the transmission and stationary states;

[0063] Establish a data life cycle management system to ensure that the creation, storage, use, archiving, and destruction of data comply with legal requirements;

[0064] Through the implementation of the above technical solutions, step S1 can effectively collect and integrate relevant data from various government functional departments and financial institutions, providing a solid data foundation for subsequent user portrait construction, behavior analysis, and strategy generation, thereby promoting the deep integration and optimization of government services and financial services.

[0065] S2. Based on the government data and financial data of enterprises and individuals, construct user portraits;

[0066] Clean and preprocess the collected government data and financial data, including removing duplicate data, handling missing values, data standardization, etc., to ensure the accuracy and reliability of subsequent analysis;

[0067] On the basis of data integration, identify and associate the same user in different data sources; involve data desensitization and anonymization processing to protect user privacy and data security;

[0068] For the construction of user portraits, extract key features from the integrated data; the extracted features include the basic information, economic activities, and financial behaviors of users;

[0069] Utilize machine learning and data mining technologies to describe the characteristics and behavior patterns of different user groups by establishing a user portrait model; the model can help understand user needs, behavior trends, and potential service preferences;

[0070] By effectively constructing and utilizing user portraits, the government and financial institutions can better understand user needs, optimize service processes, improve service efficiency and user satisfaction, thereby realizing the organic integration and optimization of government services and financial services.

[0071] S3. Input the user portrait into a pre-constructed user behavior analysis model to analyze user behavior patterns and obtain the demand hotspots of government services and financial services;

[0072] The methods for the user behavior analysis model to analyze user behavior patterns of the user portrait include:

[0073] For time series data, use time series analysis to capture user behavior trends and periodic characteristics;

[0074] Apply algorithms such as Apriori and FP-growth to discover the correlation between user behaviors, such as which government service requests often appear together with specific financial service needs;

[0075] Identify abnormal patterns in user behaviors to help prevent fraud or identify special service needs;

[0076] Cluster users according to their behavior characteristics, identify the common needs and preferences of different groups, and thus locate the hot areas of services;

[0077] Use visualization tools to display the spatio-temporal distribution of government service and financial service demands, and reveal the seasonal and regional variations of the demands;

[0078] Based on historical data and current trends, use prediction models to predict demand hotspots in the future for a period of time, providing a basis for policy-making and resource allocation;

[0079] The construction method of the user behavior analysis model includes:

[0080] Collect government data and financial data of users, clean the collected data, handle missing values and outliers, and perform data type conversion; Merge data from different sources, eliminate redundancy, and maintain data consistency;

[0081] Select a deep learning model as the basic architecture of the model, and the deep learning model includes logistic regression, random forest, support vector machine, and neural network;

[0082] Divide the dataset into a training set, a validation set, and a test set; Use the training set data to train the selected model; Use the validation set to evaluate the generalization ability of the model and avoid overfitting;

[0083] Use the test set to evaluate the model performance, paying attention to indicators such as accuracy, precision, recall rate, F1 score, and root mean square error; According to the evaluation results, adjust the model structure and parameters;

[0084] Deploy the optimized model to the production environment to analyze user behavior data in real time; Implement a monitoring mechanism to track the model performance, ensure its effectiveness on new data, and perform continuous updates according to business changes and data feedback.

[0085] S4. Generate government service strategies and financial service strategies according to the user portrait and demand hotspots;

[0086] Based on the user portrait and demand hotspots, deeply analyze the characteristics of enterprises and individuals; including their credit status, trading habits, economic strength, preferred service types, and potential financial needs, etc.; Demand hotspots involve rapid loan approval, tax planning, credit enhancement services, investment consulting, or financial services related to specific government affairs;

[0087] Use the user portrait to plan the simplest government handling process for enterprises and individuals with different needs; For enterprises that often need to handle import and export business, design a special rapid customs clearance and tax refund service process;

[0088] According to the characteristics of enterprises or individuals, automatically match applicable government subsidies and tax exemption policies, and through an intelligent prompt system, ensure that users can obtain and apply relevant policy preferences in a timely manner;

[0089] Based on factors such as the user's risk tolerance, asset size, and historical trading behavior, use machine learning algorithms to recommend the most suitable financial product portfolio;

[0090] Through data analysis, provide users with credit scores and offer credit enhancement services based on the scoring results;

[0091] Establish an intelligent customer service system, predict the problems that users may encounter according to the user profile, provide instant answers and guidance, and at the same time develop a self-service platform to enable users to conveniently complete the query, application, and management of financial products;

[0092] The strategy generation and integration in the S4 stage rely on advanced data analysis, artificial intelligence, and machine learning technologies, aiming to provide a more personalized, efficient, and integrated government service and financial service experience through a deep understanding of user characteristics and needs.

[0093] S5. Integrate the government service strategy and the financial service strategy to obtain the financial service strategy, and push the financial service strategy to the user platform;

[0094] On the basis of clarifying the government service strategy and the financial service strategy, identify the intersection points of the two to ensure that they promote and support each other; combine the fast track of government approval with the fast approval of specific financial products to form an integrated solution; at the same time, predict the possible financial service needs of users after completing a certain government affair through data analysis, and make advance arrangements to achieve seamless connection;

[0095] The methods of pushing the financial service strategy to the user platform include:

[0096] User platform interface docking: Establish secure data exchange interfaces with various user platforms to ensure that the integrated financial service strategy can be accurately transmitted to the target platform;

[0097] Personalized push strategy: Utilize the preference information in the user profile to customize the push content, time, and channels through an intelligent recommendation system to improve the acceptance and response rate of information;

[0098] Data encryption and privacy protection: Adopt industry-standard encryption technologies during data transmission and storage to ensure the security and privacy of user data;

[0099] Effect tracking and feedback loop: Establish a data monitoring system to track the execution effects of the push strategy, including indicators such as click-through rate, conversion rate, and user satisfaction, continuously optimize the push strategy, and collect user feedback to form a closed-loop optimization mechanism;

[0100] The S5 stage not only involves the strategic integration and push implementation at the technical level, but also emphasizes the user-centered design thinking, ensuring the precise push of financial service strategies, while protecting user privacy and data security, and building an efficient, secure and interactive integrated ecosystem of government services and financial services.

[0101] Embodiment 2: As Figure 2 shown, a financial service data utilization system for government service scenarios of the present invention specifically includes the following modules;

[0102] A data collection module collects government affairs data and financial data related to enterprises and individuals from various government functional departments and financial institutions; the government affairs data includes basic information data, administrative management data and economic operation data; the financial data includes transaction data, credit data, market data and user behavior data;

[0103] A user portrait construction module constructs a user portrait based on the government affairs data and financial data of enterprises and individuals;

[0104] A behavior analysis model module inputs the user portrait into a pre-constructed user behavior analysis model to analyze the user behavior pattern and obtain the demand hotspots of government service and financial service;

[0105] A strategy generation module generates government service strategies and financial service strategies according to the user portrait and demand hotspots;

[0106] A strategy integration and push module integrates the government service strategy and the financial service strategy to obtain a financial service strategy, and pushes the financial service strategy to the user platform.

[0107] This system collects government affairs and financial data from multiple sources through the data collection module, effectively breaking the information barrier between government departments and financial institutions, promoting the integration and sharing of data resources, and laying a solid foundation for in-depth analysis and strategy formulation;

[0108] The user portrait construction module constructs a detailed user portrait according to the comprehensive data set, which can more accurately understand the specific needs of enterprises and individuals, so as to provide more personalized and practical government services and financial services;

[0109] The behavior analysis model module uses advanced analysis techniques to mine the hot demand of government service and financial service from user behavior, which helps the government and financial institutions to quickly respond to market changes and layout service optimization and product innovation in advance;

[0110] The strategy generation module customizes and generates service strategies according to the user portrait and demand hotspots, which is more scientific and efficient than traditional experience judgment and can more accurately match user needs;

[0111] The Policy Integration and Push Module provides users with a one-stop solution by integrating government service and financial service policies, greatly simplifying the process for enterprises and individuals to handle business, reducing the cumbersome steps of traveling between different institutions, and enhancing the service experience and efficiency.

[0112] The system utilizes advanced technologies such as big data and artificial intelligence, which not only improves the data processing ability but also provides technical support for the innovation of government services and financial services, promotes the modern transformation of service models, and improves the overall service quality. By improving the availability of information and the transparency of services, the system enhances users' trust in the government and financial institutions, helps alleviate the information asymmetry problem, and promotes the healthy and stable development of the financial market.

[0113] In summary, through its integrated data processing, analysis, and decision-making support capabilities, the system provides a comprehensive and efficient solution to address the limitations of traditional service models, promoting the deep integration and upgrading of government services and financial services.

[0114] All the various variations and specific embodiments of the method for utilizing financial service data in a government service scenario in the foregoing Embodiment 1 are equally applicable to the system for utilizing financial service data in a government service scenario of this embodiment. Through the detailed description of the method for utilizing financial service data in a government service scenario above, those skilled in the art can clearly know the implementation method of the system for utilizing financial service data in a government service scenario in this embodiment. Therefore, for the sake of brevity of the specification, it will not be elaborated here.

[0115] In addition, this application also provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored on the memory and executable on the processor. The transceiver, the memory, and the processor are respectively connected through the bus. When the computer program is executed by the processor, it realizes each process of the method embodiment for controlling the output data and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0116] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. A method for utilizing financial service data for government service scenarios, characterized in that: The method comprises: Collect government and financial data related to enterprises and individuals from various government departments and financial institutions; Build user portraits based on corporate and personal government data and financial data; Input user portraits into the pre-built user behavior analysis model to analyze user behavior patterns and obtain demand hotspots for government services and financial services; Generate government service strategies and financial service strategies based on user portraits and demand hotspots; Integrate government service strategies and financial service strategies, obtain financial service strategies, and push financial service strategies to user platforms.

2. A method for utilizing financial service data for government service scenarios as claimed in claim 1, characterized in that: The government affairs data include basic information data, administrative management data and economic operation data.

3. A method for utilizing financial service data for government service scenarios as claimed in claim 1, characterized in that: The financial data includes transaction data, credit data, market data and user behavior data.

4. A method for utilizing financial service data for government service scenarios as claimed in claim 1, characterized in that: The methods for constructing user portraits include: Clean and pre-process the collected government and financial data, including removing duplicate data, processing missing values ​​and standardizing data; Based on data integration, identify and associate the same user in different data sources; Extract key features from the integrated data; the extracted features include basic information of users, economic activities and financial behaviors; Using machine learning and data mining techniques, a user portrait model is established to describe the characteristics and behavior patterns of different user groups.

5. A method for utilizing financial service data for government service scenarios as claimed in claim 1, characterized in that: The method for constructing the user behavior analysis model includes: Collect users' government data and financial data, clean the collected data, process missing values ​​and outliers, and convert data types; merge data from different sources to eliminate redundancy; Selecting a deep learning model as the basic architecture of the model, wherein the deep learning model includes logistic regression, random forest, support vector machine, and neural network; Divide the dataset into training set, validation set and test set; use the training set data to train the selected model; use the validation set to evaluate the generalization ability of the model; Use the test set to evaluate the model performance, focusing on accuracy, precision, recall, F1 score, and root mean square error indicators; adjust the model structure and parameters based on the evaluation results; Deploy the optimized model to the production environment and analyze user behavior data in real time.

6. A method for utilizing financial service data for government service scenarios as claimed in claim 1, characterized in that: The generation methods of government service strategies and financial service strategies include: Analyze the characteristics of enterprises and individuals based on user portraits and demand hotspots, including credit status, transaction habits, financial strength, preferred service types, and potential financial needs; Use user portraits to plan simplified government affairs processing procedures for enterprises and individuals with different needs; Automatically match applicable government subsidies and tax exemption policies based on the characteristics of enterprises and individuals; Recommend financial product portfolios using machine learning algorithms based on the user’s risk tolerance, asset size, and historical trading behavior; Through data analysis, we provide users with credit scores and provide credit enhancement services based on the scoring results.

7. A method for utilizing financial service data for government service scenarios as claimed in claim 1, characterized in that: Methods for pushing financial service strategies to user platforms include user platform interface docking, personalized push strategies, data encryption, privacy protection, effect tracking, and feedback loops.

8. A financial service data utilization system for government service scenarios, characterized in that: The system comprises: The data collection module collects government data and financial data related to enterprises and individuals from various government departments and financial institutions; the government data includes basic information data, administrative management data and economic operation data; the financial data includes transaction data, credit data, market data and user behavior data; User portrait construction module, which builds user portraits based on the government data and financial data of enterprises and individuals; The behavior analysis model module inputs user portraits into the pre-built user behavior analysis model, analyzes user behavior patterns, and obtains demand hotspots for government services and financial services; The strategy generation module generates government service strategies and financial service strategies based on user portraits and demand hotspots; The strategy fusion and push module integrates government service strategies and financial service strategies, obtains financial service strategies, and pushes financial service strategies to the user platform.

9. An electronic device for utilizing financial service data for government service scenarios, comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, and characterized in that: When the computer program is executed by the processor, the steps in the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps in the method according to any one of claims 1 to 7 are implemented.

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