Numerical model generation method and related device

Abstract

Embodiments of the present application provide a number model generation method and related equipment. The number model generation method comprises: receiving number information sent by a number terminal, the number information comprising a number type and a number of numbers; determining a target process template according to the number information, the target process template comprising a plurality of associated process nodes; determining a corresponding target number sub-model in each process node in the target process template according to the number type and the target process template; adding each target number sub-model to the corresponding process node to generate a target number model; and sending the target number model to the number terminal so that the number terminal performs number generation. This method greatly reduces the workload of developers, saves development costs, improves development efficiency, and solves the problem of high development cost and difficulty in maintaining number models in the prior art.

Description

Technical Field

[0001] This application relates to the fields of computer and communication technology, and more specifically, to a method for generating a numerical model and related equipment. Background Technology

[0002] Currently, when developers want to use the data generation model service to scrape data in the service framework, they need to manually write the entire data generation model, including the various sub-models in the data generation model and the execution order between the sub-models. In other words, developers write the code for the corresponding data generation tool, which not only faces a large development manpower cost, but also requires complex code integration to migrate the data generation tool to the service framework. The maintenance cost of the code in the later stage is also very high. Summary of the Invention

[0003] The embodiments of this application provide a method and related equipment for generating a numerical model, which can at least to some extent overcome the problems of high development cost and difficulty in maintenance of numerical models in the prior art.

[0004] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0005] According to one aspect of the embodiments of this application, a method for generating a numerical model is provided, comprising:

[0006] Receive data generation information sent by the data generation terminal, the data generation information including data generation type and number of data generation;

[0007] Based on the data generation information, a target process template is determined, which contains multiple associated process nodes;

[0008] Based on the data generation type and the target process template, determine the corresponding target data generation sub-model in each process node of the target process template;

[0009] Add each of the target data generation sub-models to the corresponding process nodes to generate the target data generation model;

[0010] The target data generation model is sent to the data generation terminal so that the data generation terminal can generate data.

[0011] In one embodiment of this application, determining a target process template based on the data generation information, wherein the target process template includes multiple associated process nodes, specifically includes:

[0012] Based on the data generation type, query the template database to obtain the initial screening process template. The initial screening process template is a process template applicable to the data generation type. All process templates in the template database are marked with the applicable data generation type.

[0013] In response to the selection of the initial screening process template, the selected initial screening process template is used as the target process template.

[0014] In one embodiment of this application, determining the matching score of each initial screening process template based on the number of fabrications specifically includes:

[0015] Based on the data generation type, query the template database to obtain the initial screening process template. The initial screening process template is a process template applicable to the data generation type. All process templates in the template database are marked with the applicable data generation type.

[0016] Based on the number of fabrications, determine the matching score for each initial screening process template;

[0017] The target process template is determined based on the matching score.

[0018] In one embodiment of this application, determining the matching score of each initial screening process template based on the number of fabrications specifically includes:

[0019] The number of fabrications and the initial screening process template are input into the scoring model, and the scoring model is input with the matching score of the initial screening process template.

[0020] In one embodiment of this application, determining the target data generation sub-model corresponding to each process node in the target process template based on the data generation type and the target process template specifically includes:

[0021] Input the data generation type and the target process template into the process recommendation model, where each process node in the target process template corresponds to a target data generation sub-model.

[0022] In one embodiment of this application, the step of adding each of the target data generation sub-models to the corresponding process node to generate the target data generation model specifically includes:

[0023] Generate identity identifiers corresponding to each of the target data creation sub-models;

[0024] Based on the identity identifier, each of the data generation sub-models is obtained from the data generation terminal;

[0025] Based on the identity identifier, each of the aforementioned data generation sub-models is added to the corresponding process node to generate the target data generation model.

[0026] In one embodiment of this application, before receiving the data generation information from the data generation terminal, wherein the data generation information includes the data generation type and the number of data generation units, the method further includes:

[0027] In response to the login operation of the data generation terminal, an account login identifier is obtained, which is generated by the data generation terminal based on the account login information;

[0028] Based on the account login identifier, query the distributed cache to obtain the account login information corresponding to the account login identifier;

[0029] Log in using the account login information so that the data generation terminal can configure the data generation information.

[0030] According to one aspect of the embodiments of this application, a method for generating a numerical model is provided, the method comprising:

[0031] The information receiving module is used to receive data generation information sent by the data generation terminal, the data generation information including data generation type and number of data generation;

[0032] The template determination module determines the target process template based on the data generation information. The target process template contains multiple associated process nodes.

[0033] The node generation module is used to determine the target data generation sub-model corresponding to each process node in the target process template based on the data generation type and the target process template.

[0034] The model generation module is used to add each of the target data generation sub-models to the corresponding process nodes to generate the target data generation model.

[0035] The data generation execution module is used to send the target data generation model to the data generation terminal so that the data generation terminal can generate data.

[0036] According to one aspect of the embodiments of this application, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the data model generation method as described in the above embodiments.

[0037] According to one aspect of the embodiments of this application, an electronic device is provided, including: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the data model generation method as described in the above embodiments.

[0038] In some embodiments of this application, the technical solutions provided involve obtaining a target process template based on data generation information at the process endpoint, and then adding corresponding target data generation sub-models to each process node of the target process template to generate the final target data generation model. This method generates a target data generation model that does not require developers to input excessive code; only the corresponding data generation information needs to be configured before model generation, significantly reducing the workload of developers, saving development costs, and improving development efficiency. Furthermore, when maintaining the target data generation model, it can be achieved directly by replacing the data generation sub-models or changing the target process template in the process nodes, reducing maintenance difficulty, saving maintenance costs, and improving maintenance efficiency. This solves the problems of high development costs and difficulty in maintaining data generation models in the prior art.

[0039] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0040] 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. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0041] Figure 1 A schematic diagram of an exemplary system architecture to which the technical solutions of the embodiments of this application can be applied is shown;

[0042] Figure 2 A flowchart illustrating the generation of a data model according to an embodiment of this application is shown.

[0043] Figure 3 It is based on Figure 2 A flowchart illustrating a specific implementation of step S200 in the numerical model generation method shown in the corresponding embodiment.

[0044] Figure 4 It is based on Figure 2 A flowchart illustrating a specific implementation of step S200 in the numerical model generation method shown in the corresponding embodiment.

[0045] Figure 5 It is based on Figure 2 A flowchart illustrating a specific implementation of step S300 in the numerical model generation method shown in the corresponding embodiment.

[0046] Figure 6 It is based on Figure 2The corresponding embodiment shows another specific implementation flowchart of the data model generation method.

[0047] Figure 7 A block diagram of a numerical model generation apparatus according to an embodiment of this application is shown schematically.

[0048] Figure 8 The structure of a computer system suitable for implementing the electronic devices of the present application is shown. Detailed Implementation

[0049] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0050] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0051] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0052] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0053] Figure 1 A schematic diagram of an exemplary system architecture to which the technical solutions of the embodiments of this application can be applied is shown.

[0054] like Figure 1 As shown, the system architecture may include terminal devices (such as...) Figure 1The device shown includes one or more of a smartphone 101, tablet 102, and portable computer 103 (which could also be a desktop computer, etc.), a network 104, and a server 105. The network 104 serves as a medium for providing a communication link between the terminal device and the server 105. The network 104 can include various connection types, such as wired communication links, wireless communication links, etc.

[0055] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, there can be any number of terminal devices, networks, and servers. For example, server 105 could be a server cluster consisting of multiple servers.

[0056] Users can interact with server 105 via network 104 using terminal devices to receive or send messages, etc. Server 105 can be a server providing various services. For example, a user uploads data creation information to server 105 using terminal device 103 (or terminal device 101 or 102). Server 105 can determine a target process template based on the data creation information, the target process template containing multiple associated process nodes; determine the corresponding target data creation sub-model in each process node of the target process template based on the data creation type and the target process template; add each target data creation sub-model to the corresponding process node to generate a target data creation model; and send the target data creation model to the data creation terminal so that the data creation terminal can perform data creation.

[0057] It should be noted that the data model generation method provided in this application embodiment is generally executed by server 105, and correspondingly, the data model generation device is generally located in server 105. However, in other embodiments of this application, the terminal device may also have similar functions to the server, thereby executing the data model generation scheme provided in this application embodiment.

[0058] The implementation details of the technical solutions in the embodiments of this application are described in detail below:

[0059] Figure 2 A flowchart of a method for generating a numerical model according to an embodiment of this application is shown. This method can be executed by a server, which may be... Figure 1 The server shown. (Refer to...) Figure 2 As shown, the method for generating the data model includes at least the following:

[0060] Step S100: Receive data generation information from the data generation terminal, wherein the data generation information includes data generation type and number of data generation.

[0061] Step S200: Based on the data generation information, determine the target process template, which contains multiple associated process nodes.

[0062] Step S300: Based on the data generation type and the target process template, determine the target data generation sub-model corresponding to each process node in the target process template.

[0063] Step S400: Add each of the target data generation sub-models to the corresponding process node to generate the target data generation model.

[0064] Step S500: Send the target data generation model to the data generation terminal so that the data generation terminal can generate data.

[0065] In this embodiment, the target process template is first determined based on the pre-configured data generation information. Then, the target data generation sub-models corresponding to each process node in the target process template are determined based on the target process objective and the data generation information. Each target data generation sub-model is then added to the corresponding process node to generate the final target data generation model. Finally, the target data generation model is sent to the data generation terminal, which can then execute the data generation steps and output a large number of generated data.

[0066] In step S100, when generating the data model, the user configures the data generation information, namely the data generation type and the number of data generated, through the data generation terminal, and then sends it to the process terminal. The data generation information includes the data generation type and the number of data generated. The data generation type refers to the type of data the user needs to use, that is, the target data generation type. The number of data generated refers to the purpose or use of the data generation.

[0067] For the same type of data production, the data production process is generally similar and can be adapted using the same process template. However, the data production process may have slight differences depending on the number of data to be produced. Therefore, in step S200, a target process template can be determined based on the data production type and the number of data to be produced.

[0068] A process template is used to nest data creation sub-models. It contains multiple related process nodes and the execution order between them. Each process node needs to contain a data creation sub-model. Once all process nodes in the process template have their corresponding data creation sub-models, a data creation model is formed. When executing a data creation model, the data creation sub-models corresponding to the process nodes are executed sequentially according to the execution order specified in the process template.

[0069] Specifically, the target process template can be determined by looking up a table or by obtaining it based on a machine learning model; this application does not limit the method.

[0070] Specifically, in some embodiments, the specific implementation of step S200 can be found in [reference needed]. Figure 3 . Figure 3 It is based on Figure 2 According to the detailed description of step S200 in the numerical model generation method shown in the corresponding embodiment, step S200 in the numerical model generation method may include the following steps:

[0071] Step S210: Based on the data generation type, query the template database to obtain the initial screening process template. The initial screening process template is a process template applicable to the data generation type. All process templates in the template database are marked with the applicable data generation type.

[0072] Step S220: Determine the matching score of each initial screening process template based on the number of fabrications.

[0073] Step S230: Determine the target process template based on the matching score.

[0074] In this embodiment, the target process template is determined by a lookup table. First, the template database is queried according to the production type to perform preliminary screening and obtain initial screening process templates. Then, the matching score of each initial screening process template is determined according to the production number. Finally, the final target process template is determined based on the matching score, thus achieving precise selection of the target process template.

[0075] In step S210, the template database is pre-configured and stores various process templates. Each process template is also marked with the applicable data generation type. Therefore, all applicable process templates can be directly filtered out based on the data generation type and output as the initial screening process templates.

[0076] In step S220, the matching degree between each initial screening process template and the number of products is determined. Specifically, the number of products and the initial screening process template can be input into the scoring model, and the scoring model is input with the matching score of the initial screening process template.

[0077] In step S230, the target process template is determined by selecting the process with the highest matching score as the target process template.

[0078] Specifically, in other embodiments, the specific implementation of step S200 can be found in [reference needed]. Figure 4 . Figure 4 It is based on Figure 2 According to the detailed description of step S200 in the numerical model generation method shown in the corresponding embodiment, step S200 in the numerical model generation method may include the following steps:

[0079] Step S201: Based on the data generation type, query the template database to obtain the initial screening process template. The initial screening process template is a process template applicable to the data generation type. All process templates in the template database are marked with the applicable data generation type.

[0080] Step S202: In response to the selection of the initial screening process template, the selected initial screening process template is used as the target process template.

[0081] In this embodiment, after selecting the initial screening process template based on the data generation type, the template is directly pushed to the client. The client then selects a suitable template from the initial screening process templates as the target process template for output. The specific method for determining this can be based on matching scores, selection by the developers, or random selection by the client.

[0082] In one embodiment, determining the target process template may include the following steps: the client determines the number of times the developer selects each process template based on previous historical records, and selects the template that the developer selects the most times as the target process template output.

[0083] Specifically, in some embodiments, the specific implementation of step S200 can be found in the following embodiments. This embodiment is based on... Figure 2 According to the detailed description of step S200 in the numerical model generation method shown in the corresponding embodiment, step S200 in the numerical model generation method may include the following steps:

[0084] The data generation information is input into the process recommendation model, and the process recommendation model outputs the target process template.

[0085] The training method for the process recommendation model specifically includes: acquiring a set of data creation information samples, wherein each data creation information sample is pre-labeled with a corresponding target process template; inputting the data of each data creation information sample into the process recommendation model to obtain the target process template output by the filtering; if the target process template obtained after inputting the data of a data creation information sample into the process recommendation model is inconsistent with the target process template pre-labeled for the data creation information sample, the filtering coefficient is adjusted until they are consistent; when the target process template obtained after inputting the data of all data creation information samples into the process recommendation model is consistent with the target process template pre-labeled for the data creation information sample, the training ends.

[0086] In some embodiments, a data creation sub-model has been placed in each process node of the determined target process template. This data creation sub-model is a recommended data creation sub-model and can be used as a reference for adding data creation sub-models to each process node.

[0087] After obtaining the target process template, in step S300, the target data sub-model for each process node is determined based on the target process template.

[0088] In the embodiments of this application, the target production number sub-model for each process node can be determined comprehensively based on the production number type, production number, and target process template. Specifically, the production number type, production number, and target process template can be input into the process recommendation model and determined by the process recommendation, or it can be determined by looking up a table or other methods.

[0089] Specifically, in some embodiments, the specific implementation of step S300 can be found in [reference needed]. Figure 5 . Figure 5 It is based on Figure 2 According to the detailed description of step S300 in the numerical model generation method shown in the corresponding embodiment, step S300 in the numerical model generation method may include the following steps:

[0090] Step S310: Determine the data creation sub-model matching result based on the data creation type and the position of the process node. The data creation sub-model matching result includes all data creation sub-models that can be filled into the process node.

[0091] Step S320: Based on the number of processes and the target process template, filter the corresponding sub-models in the sub-model matching results according to the order of the process nodes to obtain the target sub-models for each process node.

[0092] In this embodiment, the data generation sub-models that can be added to the corresponding process nodes are first screened and matched according to the data generation type and the position of the process nodes. Then, the data generation sub-models are determined as a whole according to the data generation number and the target process template to obtain the target data generation sub-models corresponding to each process node.

[0093] In step S310, the specific method for determining the matching result of the data generation sub-model based on the data generation type and the position of the process node can be to query the data generation sub-model database based on the data generation type and the position of the process node. The data generation sub-model database is pre-established and stores various data generation sub-models. Each data generation sub-model is marked with the applicable data generation type and the position of the process node into which it can be placed. Based on the data generation type and the position of the process node, the data generation sub-models that can be added to each process node can be selected.

[0094] In step S320, the screening and matching method can be to first determine the matching score of the data sub-model selected for each process node by the number of data generated, and record it as the first matching score; then determine the matching score of the data sub-model between each process node by the target process template, and record it as the second matching score; and then determine the final target data sub-model for each process node based on the first matching score and the second matching score.

[0095] Specifically, in some other embodiments, the specific implementation of step S300 can be found in the following embodiments. This embodiment is based on... Figure 2 According to the detailed description of step S300 in the numerical model generation method shown in the corresponding embodiment, step S300 in the numerical model generation method may include the following steps:

[0096] Input the data generation type and the target process template into the process recommendation model, where each process node in the target process template corresponds to a target data generation sub-model.

[0097] Specifically, the training method for the process recommendation model includes: acquiring a set of model recommendation data samples, wherein each model recommendation data sample includes information in two dimensions: data generation type and target process template, and a corresponding target data generation sub-model is pre-labeled; inputting the data of each model recommendation data sample into the process recommendation model to obtain the target data generation sub-model output by filtering; if the target data generation sub-model obtained after inputting the data of a model recommendation data sample into the process recommendation model is inconsistent with the target data generation sub-model pre-labeled for the model recommendation data sample, then adjusting the filtering coefficients until they are consistent; when the target data generation model obtained after inputting the data of all model recommendation data samples into the process recommendation model is consistent with the target data generation model pre-labeled for the model recommendation data sample, the training ends.

[0098] Specifically, in some embodiments, the specific implementation of step S300 can be found in the following embodiments. This embodiment is based on... Figure 2 According to the detailed description of step S300 in the numerical model generation method shown in the corresponding embodiment, step S300 in the numerical model generation method may include the following steps:

[0099] Based on the data generation type and target process template, the template database is queried to obtain the initial data generation sub-model, which is a data generation sub-model applicable to the data generation type and the target process template.

[0100] In response to the selection of the initial screening sub-model, the selected initial screening sub-model is used as the target sub-model.

[0101] In this embodiment, the template database is first queried according to the data generation type and target process template to obtain the initial data generation sub-model, and then the client selects the sub-model to obtain the data generation sub-model.

[0102] In some embodiments, the selection of the model can be random, in other embodiments it can be selected based on a score, and in still other embodiments it can be selected manually.

[0103] In some other embodiments, a data creation sub-model has been placed in each process node of the target process template. This data creation sub-model is a recommended data creation sub-model and can be used as a reference for adding data creation sub-models to each process node. After obtaining the initial screening sub-model, developers can replace the data creation sub-models in the process nodes according to the actual situation, which reduces the cost of generating and maintaining the data creation model.

[0104] After determining the target data generation sub-model corresponding to each process node, in step S400, a request is sent to the data generation end to obtain the corresponding target data generation sub-model, and each target data generation sub-model is added to the corresponding process node to generate the target data generation model.

[0105] Specifically, in some embodiments, the specific implementation of step S400 can be found in the following embodiments. This embodiment is based on... Figure 2 According to the detailed description of step S400 in the numerical model generation method shown in the corresponding embodiment, step S400 in the numerical model generation method may include the following steps:

[0106] Generate identity identifiers corresponding to each of the target data creation sub-models.

[0107] Based on the identity identifier, each of the data generation sub-models is obtained from the data generation terminal.

[0108] Based on the identity identifier, each of the aforementioned data generation sub-models is added to the corresponding process node to generate the target data generation model.

[0109] In this embodiment, after determining the target data generation sub-model, an identity identifier for each target data generation sub-model is first generated. This identity identifier can be a string of Uniform Resource Locator (URL), a temporary token, or a Universally Unique Identifier (UUID). Then, the processor adapter searches for the corresponding data generation sub-model on the data generation terminal based on the identity identifier and obtains the data generation sub-model. Finally, the processor mapper adds each of the data generation sub-models to the corresponding process node based on the identity identifier to generate the final target data generation model.

[0110] After obtaining the target data generation model, the target data generation model can be stored in the data generation model database or the process template database so that it can be directly called when there is a similar data generation requirement in the future.

[0111] After obtaining the target data model, in step S500, the target data model is sent to the data generation terminal so that the data generation terminal can generate data.

[0112] Please see Figure 6In some embodiments of this application, before step S100, the method further includes:

[0113] Step S101: In response to the login operation of the data generation terminal, obtain the account login identifier, which is generated by the data generation terminal based on the account login information.

[0114] Step S102: Based on the account login identifier, query the distributed cache to obtain the account login information corresponding to the account login identifier.

[0115] Step S103: Log in according to the account login information so that the data generation terminal can configure the data generation information.

[0116] In this embodiment, after a developer logs in to the data creation platform, the platform randomly generates an account login identifier, such as a token, using account login information like a UUID. This token is then associated with the account login information and stored in a distributed cache. When redirecting to the workflow platform, the workflow platform responds to the login operation of the data creation platform and receives the token. Using this token, the associated account login information can be retrieved from the distributed cache. Finally, the developer logs in using the account login information, at which point they can configure the data creation information on the data creation platform. If the workflow platform cannot retrieve the associated account login information from the distributed cache using the token, it indicates a problem with identity authentication, and an error message is displayed.

[0117] The following describes an apparatus embodiment of this application, which can be used to execute the numerical model generation method in the above embodiments of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the numerical model generation method described above.

[0118] Figure 7 A block diagram of a numerical model generation apparatus according to an embodiment of this application is shown.

[0119] Reference Figure 7 As shown, a numerical model generation apparatus 900 according to an embodiment of this application includes:

[0120] The information receiving module 910 is used to receive data generation information sent by the data generation terminal, the data generation information including data generation type and number of data generation;

[0121] The template determination module 920 determines the target process template based on the data generation information. The target process template contains multiple associated process nodes.

[0122] The node generation module 930 is used to determine the target data generation sub-model corresponding to each process node in the target process template based on the data generation type and the target process template.

[0123] The model generation module 940 is used to add each of the target data generation sub-models to the corresponding process nodes to generate the target data generation model.

[0124] The data generation execution module 950 is used to send the target data generation model to the data generation terminal so that the data generation terminal can generate data.

[0125] The specific implementation process of the functions and roles of each module in the above-mentioned device can be found in the implementation process of the corresponding steps in the above-mentioned customer screening method, and will not be repeated here.

[0126] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0127] Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0128] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, mobile terminal, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0129] Figure 8 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown.

[0130] It should be noted that, Figure 8 The computer system of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0131] like Figure 8As shown, the computer system includes a Central Processing Unit (CPU) 1801, which can perform various appropriate actions and processes based on programs stored in Read-Only Memory (ROM) 1802 or programs loaded from storage portion 1808 into Random Access Memory (RAM) 1803, such as performing the methods described in the above embodiments. The RAM 1803 also stores various programs and data required for system operation. The CPU 1801, ROM 1802, and RAM 1803 are interconnected via a bus 1804. An Input / Output (I / O) interface 1805 is also connected to the bus 1804.

[0132] The following components are connected to I / O interface 1805: an input section 1806 including a keyboard, mouse, etc.; an output section 1807 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1808 including a hard disk, etc.; and a communication section 1809 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 1809 performs communication processing via a network such as the Internet. A drive 1810 is also connected to I / O interface 1805 as needed. Removable media 1811, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 1810 as needed so that computer programs read from them can be installed into storage section 1808 as needed.

[0133] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1809, and / or installed from removable medium 1811. When the computer program is executed by central processing unit (CPU) 1801, it performs various functions defined in the system of this application.

[0134] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. The transmitted data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0135] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0136] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0137] In another aspect, this application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the methods described in the above embodiments.

[0138] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0139] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of this application.

[0140] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments 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.

[0141] 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 a numerical model, characterized in that, When applied to the process end, the data model generation method includes: Receive data generation information sent by the data generation terminal, the data generation information including data generation type and number of data generation; Based on the data generation information, a target process template is determined. This target process template contains multiple associated process nodes, each of which has a recommended data generation sub-model placed within it. The recommended data generation sub-model serves as a reference for adding each process node to the data generation sub-model. Specifically, determining the target process template includes: querying a template database based on the data generation type to obtain a preliminary screening process template. This preliminary screening process template is applicable to the data generation type, and all process templates in the template database are marked with applicable data generation types; inputting the data generation number and the preliminary screening process template into a scoring model, which outputs a matching score for the preliminary screening process template; and determining the target process template based on the matching score. Based on the data generation type and the target process template, determine the target data generation sub-model corresponding to each process node in the target process template; By replacing the recommended data generation sub-models in the process nodes of the target process template, each target data generation sub-model is added to the corresponding process node to generate the target data generation model. The target data generation model is sent to the data generation terminal so that the data generation terminal can generate data.

2. The method for generating a numerical model as described in claim 1, characterized in that, The step of determining a target process template based on the data generation information, wherein the target process template contains multiple associated process nodes, specifically including: Based on the data generation type, query the template database to obtain the initial screening process template. The initial screening process template is a process template applicable to the data generation type. All process templates in the template database are marked with the applicable data generation type. In response to the selection of the initial screening process template, the selected initial screening process template is used as the target process template.

3. The method for generating a numerical model as described in claim 1, characterized in that, The step of determining the target data generation sub-model corresponding to each process node in the target process template based on the data generation type and the target process template specifically includes: The data generation type and the target process template are input into the process recommendation model, and the process recommendation model outputs the target data generation sub-model corresponding to each process node in the target process template.

4. The method for generating a numerical model as described in claim 1, characterized in that, The step of adding each of the target data generation sub-models to the corresponding process node to generate the target data generation model specifically includes: Generate identity identifiers corresponding to each of the target data creation sub-models; Based on the identity identifier, each target data generation sub-model is obtained from the data generation terminal; Based on the identity identifier, each of the target data generation sub-models is added to the corresponding process node to generate the target data generation model.

5. The method for generating a numerical model as described in claim 1, characterized in that, Before receiving the data generation information from the data generation terminal, wherein the data generation information includes the data generation type and the number of data generation units, the method further includes: In response to the login operation of the data generation terminal, an account login identifier is obtained, which is generated by the data generation terminal based on the account login information; Based on the account login identifier, query the distributed cache to obtain the account login information corresponding to the account login identifier; Log in using the account login information so that the data generation terminal can configure the data generation information.

6. A device for generating numerical models, characterized in that, The data model generation device includes: The information receiving module is used to receive data generation information sent by the data generation terminal, the data generation information including data generation type and number of data generation; The template determination module determines a target process template based on the data generation information. The target process template contains multiple associated process nodes, each of which has a recommended data generation sub-model placed within it. These recommended sub-models serve as a reference for adding each process node to the data generation sub-model. Specifically, determining the target process template includes: querying a template database based on the data generation type to obtain a preliminary screening process template. This preliminary screening process template is applicable to the data generation type, and all process templates in the template database are marked with applicable data generation types; inputting the data generation number and the preliminary screening process template into a scoring model, which outputs a matching score for the preliminary screening process template; and determining the target process template based on the matching score. The node generation module is used to determine the target data generation sub-model corresponding to each process node in the target process template based on the data generation type and the target process template. The model generation module is used to replace the recommended data creation sub-models in the process nodes of the target process template, so as to add each of the target data creation sub-models to the corresponding process nodes and generate a target data creation model. The data generation execution module is used to send the target data generation model to the data generation terminal so that the data generation terminal can generate data.

7. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method for generating a numerical model as described in any one of claims 1 to 5.

8. An electronic device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the data model generation method as described in any one of claims 1 to 5.

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