Business case generation method, apparatus, device, storage medium and program product

Abstract

The application provides a business use case generation method and device, equipment, storage medium and program product, relates to the field of artificial intelligence, and in particular to the application of a large model in the field of financial technology and software testing. The method comprises the following steps: in response to business requirement information input by a user, determining historical use cases matched with the business requirement information from a historical use case database, and obtaining first use case attribute information corresponding to the historical use cases; calling an attribute information generation model based on the business requirement information to generate second use case attribute information corresponding to the business requirement information; obtaining statistical information of the first use case attribute information and statistical information of the second use case attribute information, and determining target use case attribute information according to the statistical information of the first use case attribute information and the statistical information of the second use case attribute information; and calling a preset use case generation model according to the target use case attribute information to generate a business use case meeting the business requirement information. The method can improve the generation efficiency of the business use case.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence, specifically the application of large models in fintech and software testing, and particularly to a method, apparatus, device, storage medium, and program product for generating business use cases. Background Technology

[0002] Currently, with the rapid development of the financial industry, users' business needs are increasing. Therefore, in order to meet these needs, it is necessary to generate business use cases that describe those needs, and then develop the business based on these use cases.

[0003] In related technologies, staff write business use cases based on business requirements. Each business use case needs to describe a complete business process.

[0004] However, the inventors have discovered at least the following technical problems in the related technology: due to the large amount of content involved in business use cases, the time spent writing business use cases is long and the efficiency is low. Summary of the Invention

[0005] This application provides a method, apparatus, device, storage medium, and program product for generating business use cases, in order to solve the technical problem of low efficiency in manually generating business use cases in the prior art.

[0006] Firstly, this application provides a method for generating business use cases, including:

[0007] In response to the business requirement information input by the user, the system determines the historical use case that matches the business requirement information from the historical use case database and obtains the first use case attribute information corresponding to the historical use case.

[0008] Based on the business requirement information, the attribute information generation model is invoked to generate the second use case attribute information corresponding to the business requirement information;

[0009] Obtain statistical information of the first use case attribute information and statistical information of the second use case attribute information, and determine the target use case attribute information based on the statistical information of the first use case attribute information and the statistical information of the second use case attribute information, wherein the statistical information is used to indicate the number of times the use case attribute information is used;

[0010] Based on the target use case attribute information, a preset use case generation model is invoked to generate business use cases that meet the business requirements information.

[0011] Secondly, this application provides a business use case generation apparatus, comprising:

[0012] The determination module is used to respond to the business requirement information input by the user, determine the historical use case that matches the business requirement information from the historical use case database, and obtain the first use case attribute information corresponding to the historical use case.

[0013] The first generation module is used to call the attribute information generation model based on the business requirement information to generate the second use case attribute information corresponding to the business requirement information.

[0014] The acquisition module is used to acquire statistical information of the first use case attribute information and statistical information of the second use case attribute information, and determine the target use case attribute information based on the statistical information of the first use case attribute information and the statistical information of the second use case attribute information, wherein the statistical information is used to indicate the number of times the use case attribute information is used;

[0015] The second generation module is used to call a preset use case generation model based on the target use case attribute information to generate business use cases that meet the business requirements information.

[0016] Thirdly, this application provides an electronic device, including: a memory and a processor;

[0017] The memory stores the instructions that the computer executes;

[0018] The processor executes computer execution instructions stored in memory, causing the processor to perform the implementation method described in the first aspect above.

[0019] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the embodiments described in the first aspect above.

[0020] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, is used to implement the embodiments described in the first aspect above.

[0021] This application provides a method, apparatus, device, storage medium, and program product for generating business use cases. The method includes: responding to business requirement information input by a user; determining historical use cases matching the business requirement information from a historical use case database; obtaining first use case attribute information corresponding to the historical use cases; invoking an attribute information generation model based on the business requirement information to generate second use case attribute information corresponding to the business requirement information; obtaining statistical information of the first and second use case attribute information, and determining target use case attribute information based on the statistical information of the first and second use case attribute information, wherein the statistical information represents the number of times the use case attribute information is used; and invoking a preset use case generation model based on the target use case attribute information to generate business use cases that conform to the business requirement information. In this embodiment, by first obtaining historical use cases and model-generated use cases, and then using the historical and model-generated use cases to invoke a preset use case generation model to automatically generate business use cases that conform to the business requirement information, the efficiency of business use case generation is improved compared to manual generation. Attached Figure Description

[0022] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0023] Figure 1 A schematic diagram illustrating an application scenario of a method for generating business use cases provided in an embodiment of this application;

[0024] Figure 2 The flow of a business use case generation method provided in this application embodiment Figure 1 ;

[0025] Figure 3 A schematic diagram of a method for generating business use cases provided in an embodiment of this application. Figure 1 ;

[0026] Figure 4 A schematic diagram of the structure of a business use case generation device provided in an embodiment of this application;

[0027] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0028] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0029] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0030] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of the relevant data all comply with the relevant laws, regulations, and standards of the relevant countries and regions, have taken necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation portals for users to choose to authorize or refuse.

[0031] Furthermore, the technical solution involved in this application, which involves big data analysis of user information (including but not limited to personal biometrics, identity data, consumption data, asset data, electronic terminal operation data, etc.) and the use of artificial intelligence technology for automated decision-making, and makes decisions that have a significant impact on personal rights based on the results of automated decision-making, provides users with corresponding operation entry points for users to choose to agree to or reject the results of automated decision-making; if the user chooses to reject, the process will proceed to the expert decision-making process.

[0032] It should be noted that the business use case generation method, apparatus, device, storage medium and program product provided in this application can be used in the field of financial technology, or in any field other than financial technology. The application field of the business use case generation method, apparatus, device, storage medium and program product in this application is not limited.

[0033] Currently, with the rapid development of the financial industry, users' business needs are increasing. Therefore, in order to meet these needs, it is necessary to generate business use cases that describe those needs, and then develop the business based on these use cases.

[0034] In related technologies, staff write business use cases based on business requirements. Each business use case needs to describe a complete business process. However, because business use cases involve a lot of content—for example, a single business use case often contains ten chapters and over a hundred fields—the workload is substantial, making it time-consuming and labor-intensive for business personnel. This results in a long development time and low efficiency in writing business use cases.

[0035] Therefore, improving the efficiency of business use case generation is a pressing technical problem that needs to be solved.

[0036] To address the aforementioned technical problems, the inventors' technical concept is as follows: Utilizing an artificial intelligence model, business use cases are intelligently generated through a brief use case overview, thereby improving the efficiency of business use case generation. Business personnel can also confirm or modify these use cases to improve their accuracy.

[0037] Accordingly, the specific steps may include: First, in response to the business requirement information input by the user, determining historical use cases that match the business requirement information from the historical use case database, and obtaining the first use case attribute information corresponding to the historical use cases; then, invoking the attribute information generation model based on the business requirement information to generate the second use case attribute information corresponding to the business requirement information. Next, obtaining statistical information on the first and second use case attribute information, and determining the target use case attribute information based on the statistical information of the first and second use case attribute information, whereby the statistical information represents the number of times the use case attribute information is used. Finally, invoking a preset use case generation model based on the target use case attribute information to generate business use cases that conform to the business requirement information.

[0038] In this technical solution, by first acquiring historical use cases and model-generated use cases, and then using the historical use cases and model-generated use cases to call a preset use case generation model, business use cases that meet business requirements are automatically generated. Compared with manually generating business use cases, this improves the efficiency of business use case generation.

[0039] Figure 1 This is a schematic diagram illustrating an application scenario for a method for generating business use cases provided in an embodiment of this application. For example... Figure 1 As shown, terminal 101 and server 102 are connected via a network. Users can send use case generation requests and business requirement information to server 102 through terminal 101. Server 102 receives the use case generation request and can generate business use cases that conform to the business requirement information using the business use case generation method provided in this application. Server 102 returns the generated business use cases to terminal 101 for display.

[0040] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0041] Figure 2 The flow of a business use case generation method provided in this application embodiment Figure 1 ,like Figure 2 As shown, the method includes:

[0042] S201. In response to the business requirement information input by the user, determine the historical use case that matches the business requirement information from the historical use case database, and obtain the first use case attribute information corresponding to the historical use case.

[0043] In this embodiment of the disclosure, the business requirement information may be a brief description of a use case. For example, the business requirement information may be "We need to launch an online fast-track application channel for credit cards for our customers."

[0044] In some embodiments, semantic text vectors of business requirement information can be determined using natural language processing techniques, and historical use cases matching the business requirement information can be determined from a historical use case database using these semantic text vectors. Accordingly, determining historical use cases matching the business requirement information from the historical use case database in response to user-inputted business requirement information includes: semantically analyzing the business requirement information in response to user-inputted business requirement information to obtain semantic text vector information; and determining historical use cases matching the business requirement information from the historical use case database based on the semantic text vector information.

[0045] Optionally, based on the semantic text vector information, the similarity between the semantic text vector information and the text vector information of historical use cases can be calculated through a vectorization model. The historical use case with the highest similarity can be selected from the historical use case database and identified as the historical use case that matches the business requirement information.

[0046] The text vector information of historical use cases can include text vector information corresponding to use case type information, text vector information corresponding to architecture type information, text vector information corresponding to channel type information, text vector information corresponding to customer type information, and text vector information corresponding to use case description information.

[0047] In some embodiments, the similarity between semantic text vector information and each individual text vector information can be calculated, and the sum of the similarities can be determined as the similarity between the semantic text vector information and the text vector information of historical use cases. In other embodiments, weights can be set for each text vector information, and the similarity between the semantic text vector information and the text vector information of historical use cases can be obtained by weighted summation based on the similarity between each text vector information and its weight.

[0048] In some embodiments, the historical use case database stores a correspondence between use case identifiers and use case attribute information. Accordingly, the first use case attribute information corresponding to the historical use case can be determined from the stored correspondence between use case identifiers and use case attribute information using the target use case identifier corresponding to the aforementioned historical use case.

[0049] Optionally, the first use case attribute information includes one or more of the following: use case type information, architecture type information, channel type information, customer type information, and use case description information.

[0050] The information includes the following components: Use Case Type Information, which indicates the type of use case; for example, use case type information includes: management, query, transaction, approval, etc.; Architecture Type Information, which indicates the business system; for example, architecture type information includes: credit system, payment and settlement system, customer management system; Channel Type Information, which indicates the transaction channel; for example, channel type information includes: mobile banking, third-party payment, counter service, etc.; and Customer Type Information, which indicates the customer category; for example, customer type information includes: individual customers, corporate customers, high-credit customers, etc.

[0051] S202. Based on the business requirement information, call the attribute information generation model to generate the second use case attribute information corresponding to the business requirement information.

[0052] In some embodiments, the attribute information generation model can be directly invoked to generate the second use case attribute information corresponding to the business requirement information.

[0053] In another embodiment, corresponding prompt words can be generated based on business requirement information. Then, the attribute information generation model is invoked using the prompt words to generate second use case attribute information corresponding to the business requirement information. Accordingly, this step may include: invoking the attribute information generation model based on the business requirement information to generate prompt words corresponding to the business requirement information; and invoking the attribute information generation model based on the prompt words corresponding to the business requirement information to generate second use case attribute information corresponding to the business requirement information.

[0054] Optionally, the prompt information includes one or more of the following: scenario information, business object information, function information, and operation information. Scenario information indicates the timing, conditions, or prerequisites for the operation. For example, the scenario information could be: "After loan approval." Business object information represents the business object, such as a loan contract or electronic account. Function information represents the business function, such as an online credit card application channel. Operation information represents the type of business operation, such as creation, modification, query, or approval.

[0055] Optionally, the prompt word information is input into the attribute information generation model, and the output is the second use case attribute information corresponding to the business requirement information. The second use case attribute information includes one or more of the following: use case type information, architecture type information, channel type information, customer type information, and use case description information.

[0056] S203. Obtain statistical information of the first use case attribute information and statistical information of the second use case attribute information, and determine the target use case attribute information based on the statistical information of the first use case attribute information and the statistical information of the second use case attribute information. The statistical information is used to indicate the number of times the use case attribute information is used.

[0057] In some embodiments, statistics are used to represent the number of times use case attribute information is used; accordingly, determining target use case attribute information based on statistics of first use case attribute information and statistics of second use case attribute information includes: if statistics of first use case attribute information are greater than statistics of second use case attribute information, then the first use case attribute information is determined as target use case attribute information; if statistics of first use case attribute information are less than or equal to statistics of second use case attribute information, then the second use case attribute information is determined as target use case attribute information.

[0058] In other embodiments, statistical information is used to represent the number of positive examples, where the number of positive examples includes the number of uses and / or the number of likes. In this case, the use case attribute information with a larger number of positive examples can be determined as the target use case attribute information by using the number of positive examples in the first use case attribute information and the number of positive examples in the second use case attribute information.

[0059] S204. Based on the target use case attribute information, call the preset use case generation model to generate business use cases that meet the business requirements.

[0060] In some embodiments, the use case generation model includes a business process information generation model, a business rule information generation model, and a business risk information generation model; correspondingly, this step includes: based on the target use case attribute information, calling the business process information generation model, the business rule information generation model, and the business risk information generation model to generate use case field information; and based on the use case field information, calling the field mapping module to generate business use cases that meet business requirements.

[0061] Optionally, the use case field information includes business process description field information, business rule description field information, and business risk description field information. The field mapping module can convert the business process description field information, business rule description field information, and business risk description field information into business process fields, business rule fields, and business risk fields in the business use case.

[0062] In some embodiments, the business process generation module, business rule generation module, and business risk generation module can be invoked respectively based on the target use case attribute information to generate business process description field information, business rule description field information, and business risk description field information.

[0063] It should be noted that the business process information generation model, business rule information generation model, and business risk information generation model can be used as independent intelligent generation models.

[0064] In some embodiments, such as Figure 3 As shown, after generating business use cases, the system can also call the rule checking module to check whether the business use cases match the user input. If they match, the storage module is called to store them in the database; otherwise, they are regenerated.

[0065] In some embodiments, such as Figure 3 As shown, after generating business use cases, the front-end display module can be called to retrieve the business use cases and display them on the page so that users can view business use cases containing multiple fields of information.

[0066] This application provides a method for generating business use cases: First, in response to user-inputted business requirement information, historical use cases matching the business requirement information are determined from a historical use case database, and first use case attribute information corresponding to the historical use cases is obtained. Based on the business requirement information, an attribute information generation model is invoked to generate second use case attribute information corresponding to the business requirement information. Then, statistical information of the first and second use case attribute information is obtained, and target use case attribute information is determined based on this statistical information. The statistical information represents the number of times the use case attribute information is used. Finally, a preset use case generation model is invoked based on the target use case attribute information to generate business use cases that conform to the business requirement information. In this embodiment, by first obtaining historical use cases and model-generated use cases, and then using these historical and model-generated use cases to invoke a preset use case generation model to automatically generate business use cases that conform to the business requirement information, the efficiency of business use case generation is improved compared to manual generation.

[0067] Figure 4 A schematic diagram of the structure of a business use case generation device provided in an embodiment of this application. Figure 1 ,like Figure 4 As shown, the device includes:

[0068] The determination module 401 is used to respond to the business requirement information input by the user, determine the historical use case that matches the business requirement information from the historical use case database, and obtain the first use case attribute information corresponding to the historical use case.

[0069] The first generation module 402 is used to call the attribute information generation model based on the business requirement information to generate the second use case attribute information corresponding to the business requirement information.

[0070] The acquisition module 403 is used to acquire statistical information of the first use case attribute information and statistical information of the second use case attribute information, and to determine the target use case attribute information based on the statistical information of the first use case attribute information and the statistical information of the second use case attribute information. The statistical information is used to indicate the number of times the use case attribute information is used.

[0071] The second generation module 404 is used to call a preset use case generation model based on the target use case attribute information to generate business use cases that meet business requirements.

[0072] In one possible implementation, the first generation module 402 calls the attribute information generation model based on the business requirement information to generate second use case attribute information corresponding to the business requirement information, including: calling the attribute information generation model based on the business requirement information to generate prompt word information corresponding to the business requirement information; and calling the attribute information generation model based on the prompt word information corresponding to the business requirement information to generate second use case attribute information corresponding to the business requirement information.

[0073] In one possible implementation, the prompt information includes one or more of the following: scene information, business object information, function information, and operation information.

[0074] In one possible implementation, the determining module 401, in response to user-inputted business requirement information, determines historical use cases that match the business requirement information from a historical use case database, including: in response to user-inputted business requirement information, performing semantic analysis on the business requirement information to obtain semantic text vector information; and determining historical use cases that match the business requirement information from the historical use case database based on the semantic text vector information.

[0075] In one possible implementation, the acquisition module 403 determines the target use case attribute information based on the statistical information of the first use case attribute information and the statistical information of the second use case attribute information, including: if the statistical information of the first use case attribute information is greater than the statistical information of the second use case attribute information, then the first use case attribute information is determined as the target use case attribute information; if the statistical information of the first use case attribute information is less than or equal to the statistical information of the second use case attribute information, then the second use case attribute information is determined as the target use case attribute information.

[0076] In one possible implementation, the use case generation model includes a business process information generation model, a business rule information generation model, and a business risk information generation model; the second generation module 404 calls a preset use case generation model based on the target use case attribute information to generate business use cases that meet business requirements, including: calling the business process information generation model, the business rule information generation model, and the business risk information generation model based on the target use case attribute information to generate use case field information; and calling the field mapping module based on the use case field information to generate business use cases that meet business requirements.

[0077] In one possible implementation, the first use case attribute information includes one or more of use case type information, architecture type information, channel type information, customer type information, and use case description information; the second use case attribute information includes one or more of use case type information, architecture type information, channel type information, customer type information, and use case description information.

[0078] This application provides a business use case generation device that first obtains historical use cases and model-generated use cases, and then uses the historical use cases and model-generated use cases to call a preset use case generation model to automatically generate business use cases that meet business requirements. Compared with manually generating business use cases, this improves the efficiency of business use case generation.

[0079] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 5 As shown, the electronic device 500 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the device 500 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus 504.

[0080] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0081] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0082] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0083] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0084] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0085] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0086] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0087] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0088] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0089] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0090] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0091] It should be noted that the terms "first," "second," etc., in the claims, specification, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, products, or apparatus.

[0092] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, or integrated into another system, or some features may be ignored or not executed.

[0093] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0094] When integrated units / modules are implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0095] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0096] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0097] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0098] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for generating business use cases, characterized in that, The method includes: In response to the business requirement information input by the user, the system determines the historical use case that matches the business requirement information from the historical use case database and obtains the first use case attribute information corresponding to the historical use case. Based on the business requirement information, the attribute information generation model is invoked to generate the second use case attribute information corresponding to the business requirement information; Obtain statistical information of the first use case attribute information and statistical information of the second use case attribute information, and determine the target use case attribute information based on the statistical information of the first use case attribute information and the statistical information of the second use case attribute information, wherein the statistical information is used to indicate the number of times the use case attribute information is used; Based on the target use case attribute information, a preset use case generation model is invoked to generate business use cases that meet the business requirements information.

2. The generation method according to claim 1, characterized in that, The step of calling the attribute information generation model based on the business requirement information to generate second use case attribute information corresponding to the business requirement information includes: Based on the business requirement information, the attribute information generation model is invoked to generate prompt word information corresponding to the business requirement information; Based on the prompt word information corresponding to the business requirement information, the attribute information generation model is invoked to generate the second use case attribute information corresponding to the business requirement information.

3. The generation method according to claim 2, characterized in that, The prompt information includes one or more of the following: scene information, business object information, function information, and operation information.

4. The generation method according to claim 1, characterized in that, The process of responding to user-inputted business requirement information and determining historical use cases that match the business requirement information from a historical use case database includes: In response to the business requirement information input by the user, semantic analysis is performed on the business requirement information to obtain semantic text vector information; Based on the semantic text vector information, historical use cases that match the business requirement information are determined from the historical use case database.

5. The generation method according to claim 1, characterized in that, The determination of target use case attribute information based on the statistical information of the first use case attribute information and the statistical information of the second use case attribute information includes: If the statistical information of the first use case attribute information is greater than the statistical information of the second use case attribute information, then the first use case attribute information is determined as the target use case attribute information; If the statistical information of the first use case attribute information is less than or equal to the statistical information of the second use case attribute information, then the second use case attribute information is determined as the target use case attribute information.

6. The generation method according to claim 1, characterized in that, The use case generation model includes a business process information generation model, a business rule information generation model, and a business risk information generation model. The step of calling a preset use case generation model based on the target use case attribute information to generate business use cases that conform to the business requirements information includes: Based on the target use case attribute information, the business process information generation model, business rule information generation model, and business risk information generation model are invoked to generate use case field information; The field mapping module is invoked based on the use case field information to generate business use cases that meet the business requirements.

7. The generation method according to any one of claims 1-6, characterized in that, The first use case attribute information includes one or more of the following: use case type information, architecture type information, channel type information, customer type information, and use case description information; the second use case attribute information includes one or more of the following: use case type information, architecture type information, channel type information, customer type information, and use case description information.

8. A device for generating business use cases, characterized in that, The device includes: The determination module is used to respond to the business requirement information input by the user, determine the historical use case that matches the business requirement information from the historical use case database, and obtain the first use case attribute information corresponding to the historical use case. The first generation module is used to call the attribute information generation model based on the business requirement information to generate the second use case attribute information corresponding to the business requirement information. The acquisition module is used to acquire statistical information of the first use case attribute information and statistical information of the second use case attribute information, and determine the target use case attribute information based on the statistical information of the first use case attribute information and the statistical information of the second use case attribute information, wherein the statistical information is used to indicate the number of times the use case attribute information is used; The second generation module is used to call a preset use case generation model based on the target use case attribute information to generate business use cases that meet the business requirements information.

9. An electronic device, characterized in that, The electronic device includes: a memory and a processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the business use case generation method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method for generating business use cases as described in any one of claims 1-7.

11. A computer program product comprising a computer program that, when executed by a processor, implements the method for generating business use cases as described in any one of claims 1-7.

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