Modeling method and question and answer method

Abstract

The invention provides a modeling method and a question answering method, and relates to the technical field of data processing. The method comprises the following steps: acquiring a to-be-identified business requirement document, and acquiring a plurality of to-be-extracted model element types; extracting a model element corresponding to any model element type from the business requirement document through an identification model; wherein the model elements have corresponding element information; and constructing the business model to be constructed according to the element information of each model element. Therefore, the model elements in the business demand document are quickly positioned and extracted through the automatic recognition model, the problem of low manual recognition efficiency is solved, the time for manually reading and analyzing the document is shortened, the construction speed of the business model is increased, the construction efficiency of the model is improved, and the construction efficiency of the business model is improved due to reduction of manual intervention. Misunderstanding or omission possibly occurring during manual extraction is avoided, and the accuracy of the model is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technologies, and in particular, to a modeling method and a question-answering method. Background Art

[0002] Business modeling is a professional and complex task that requires identifying, abstracting, and extracting business models from a large number of sources such as asset documents and system data. Currently, these tasks in the business modeling process mainly rely on human labor. However, the complexity and time-consuming nature of this process, as well as its extremely high requirements for the professionalism and experience of staff, have made business modeling a very challenging task. Summary of the Invention

[0003] The present disclosure aims to at least partly solve one of the technical problems in the related art.

[0004] One aspect of the present disclosure provides a modeling method and apparatus, which can quickly locate and extract model elements in a business requirements document through an automated recognition model, solve the problem of low efficiency of manual recognition, reduce the time for manual reading and parsing of documents, thereby accelerating the construction speed of the business model, improving the construction efficiency of the model, and since manual intervention is reduced, misunderstandings or omissions that may occur during manual extraction are avoided, and the accuracy of the model is improved.

[0005] The first aspect embodiment of the present disclosure provides a modeling method, including:

[0006] Obtaining a business requirements document to be recognized, and obtaining a plurality of model element types to be extracted;

[0007] Extracting, from the business requirements document, model elements corresponding to any one of the model element types through a recognition model; wherein, the model elements have corresponding element information;

[0008] Constructing a business model to be constructed according to the element information of each of the model elements.

[0009] The second aspect embodiment of the present disclosure provides a question-answering method, including:

[0010] Obtaining a target question in the field of business modeling;

[0011] Generating an answer to the target question based on the business model constructed by the modeling method provided in the first aspect embodiment of the present disclosure.

[0012] The third aspect embodiment of the present disclosure provides a modeling apparatus, including:

[0013] An obtaining module, configured to obtain a business requirements document to be recognized, and obtain a plurality of model element types to be extracted;

[0014] An extraction module, configured to extract model elements corresponding to any one of the model element types from the business requirement document through an identification model; wherein, the model elements have corresponding element information.

[0015] A construction module, configured to construct a business model to be constructed according to the element information of each model element.

[0016] An embodiment of the fourth aspect of the present disclosure provides a question-answering device, including:

[0017] An acquisition module, configured to acquire business questions.

[0018] A generation module, configured to generate an answer to the business question based on the business model constructed by the modeling method proposed in the embodiment of the first aspect of the present disclosure.

[0019] An embodiment of the fifth aspect of the present disclosure provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the modeling method proposed in the embodiment of the first aspect of the present disclosure and / or the question-answering method proposed in the embodiment of the second aspect are implemented.

[0020] An embodiment of the sixth aspect of the present disclosure provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the modeling method proposed in the embodiment of the first aspect of the present disclosure and / or the question-answering method proposed in the embodiment of the second aspect are implemented.

[0021] An embodiment of the seventh aspect of the present disclosure provides a computer program product. When the instructions in the computer program product are executed by a processor, the modeling method proposed in the embodiment of the first aspect of the present disclosure and / or the question-answering method proposed in the embodiment of the second aspect are executed.

[0022] The technical solutions provided in the above embodiments of the present disclosure at least bring the following beneficial effects:

[0023] Obtain the business requirement document to be recognized, and obtain multiple model element types to be extracted; extract model elements corresponding to any model element type from the business requirement document through an identification model; wherein, the model elements have corresponding element information; construct the business model to be constructed according to the element information of each model element. Thus, by using the automated identification model to quickly locate and extract model elements in the business requirement document, the problem of low manual identification efficiency is solved, the time for manual reading and parsing the document is reduced, thereby accelerating the construction speed of the business model, improving the construction efficiency of the model, and since manual intervention is reduced, misunderstandings or omissions that may occur during manual extraction are avoided, improving the accuracy of the model; further, by performing content optimization on the element information of the model elements, the data accuracy, integrity, consistency, etc. of the model elements can be improved, the data quality of the model elements can be enhanced, and thus the reliability of the constructed business model can be improved. At the same time, with the help of the optimization model, the automated optimization of the element information of the model elements is realized, manual intervention is reduced, errors caused by human factors are reduced, and the work efficiency is improved; by checking whether there is historical data conflicting with the model elements in the target database, data inconsistency problems can be discovered and solved in a timely manner, and the overall consistency of the data can be maintained; by automatically generating multiple candidate names for the model elements through the target model, more choices are provided for users, which helps to meet naming preferences in different scenarios.

[0024] Additional aspects and advantages of the present disclosure will be given in part in the following description, will become apparent in part from the following description, or will be understood through the practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The above and / or additional aspects and advantages of the present disclosure will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, wherein:

[0026] Figure 1 is a schematic flowchart of a modeling method provided by an embodiment of the present disclosure;

[0027] Figure 2 is a schematic flowchart of another modeling method provided by an embodiment of the present disclosure;

[0028] Figure 3 is a schematic flowchart of another modeling method provided by an embodiment of the present disclosure;

[0029] Figure 4 is a schematic flowchart of another modeling method provided by an embodiment of the present disclosure;

[0030] Figure 5 is a schematic flowchart of another modeling method provided by an embodiment of the present disclosure;

[0031] Figure 6A flowchart of a question-answering method provided by an embodiment of the present disclosure;

[0032] Figure 7 A flowchart of a modeling method provided by an embodiment of the present disclosure;

[0033] Figure 8 A structural diagram of a modeling device provided by an embodiment of the present disclosure;

[0034] Figure 9 A structural diagram of a question-answering device provided by an embodiment of the present disclosure;

[0035] Figure 10 It is a structural diagram of an electronic device shown in an exemplary embodiment of the present disclosure. Detailed implementation manners

[0036] The embodiments of the present disclosure will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present disclosure, and should not be construed as a limitation of the present disclosure.

[0037] Business modeling is a highly challenging task. Currently, business modeling mainly relies on manual work, which leads to a high dependence on modelers in the business modeling process, and requires modelers to have rich professional knowledge and practical experience to accurately understand and abstract business logic. However, business modeling is also a time-consuming task. Specifically, for structured business requirement documents, it takes a lot of time to identify data model elements from structured business requirement documents, even for experienced modelers; for unstructured documents, due to more scattered and complex information, the difficulty and time cost of identifying and extracting raw data will increase significantly. At the same time, business modeling is a costly task. The high labor cost is an important burden in the business modeling process, and due to the long modeling process, the project cycle is extended, thus increasing the overall cost.

[0038] It has been experimentally proven that it takes at least 8 hours for a professional modeler with 3 - 5 years of experience to identify approximately 300 data model elements from a 10,000-word structured business requirement document alone. And for identifying and extracting raw data from a document containing a lot of unstructured data, the requirements for the professionalism and experience of the modeler are even higher and more, and the corresponding cost will also increase a lot. When the business model data volume of an enterprise is very large, if the entire enterprise's business modeling is to be completed, a large amount of manpower and time need to be invested to sort out, abstract, and input data.

[0039] In view of at least one of the above problems, the present disclosure provides a modeling method and a question-answering method.

[0040] The following describes the modeling method and the question-answering method according to embodiments of the present disclosure with reference to the accompanying drawings.

[0041] Figure 1 It is a schematic flowchart of a modeling method provided by an embodiment of the present disclosure.

[0042] In the embodiments of the present disclosure, it is exemplified that the modeling method is configured in a modeling device, and the modeling device can be applied to any electronic device so that the electronic device can perform a modeling function.

[0043] Among them, the electronic device can be any device with computing capabilities, such as a personal computer, a mobile terminal, a server, etc. The mobile terminal can be, for example, a mobile phone, a tablet computer, a personal digital assistant, a wearable device, etc., which are hardware devices with various operating systems, touch screens, and / or display screens.

[0044] As Figure 1 shown, the modeling method includes the following steps S101 to S103:

[0045] Step S101, obtain a business requirement document to be recognized, and obtain a plurality of model element types to be extracted.

[0046] Among them, the business requirement document is used to describe the business requirements put forward by relevant enterprises for products, services, processes, etc. to achieve specific business goals or solve specific business problems. It should be noted that the present disclosure does not limit the document format of the business requirement document. For example, the document format of the business requirement document is DOC format, or PDF (Portable Document Format) format, etc. It should also be noted that the present disclosure does not limit the number of business requirement documents to be recognized.

[0047] Among them, the model element types include, but are not limited to, activities, tasks, steps, basic products, product conditions, business entities, entity relationships, etc.

[0048] In order to effectively obtain the business requirement document to be recognized, as a possible implementation, in response to a user operation, obtain the business requirement document to be recognized from local storage. Among them, the user operation includes, but is not limited to, an input operation, a click operation, etc.

[0049] As another possible implementation, the business requirement document can also be obtained by manual upload.

[0050] To quickly and accurately obtain multiple model element types to be extracted, as a possible implementation, read and display multiple preset element types in an element type library, and in response to a user's selection operation, determine multiple model element types from the multiple preset element types. Herein, the preset element types are pre-set, and the present disclosure places no restrictions on the setting of the preset element types.

[0051] That is to say, there are multiple preset element types in the element type library. The multiple preset element types in the element type library can be read and displayed. After the user selects a preset element type from the displayed multiple preset element types, in response to the user's selection operation, the preset element type selected by the user can be determined as the model element type.

[0052] As another possible implementation, it is also possible to obtain multiple model element types in response to a user's input operation. Specifically, by the user inputting multiple element types, the multiple element types input by the user are determined as multiple model element types. Herein, the input operation includes keyboard input, voice input, mouse input, touch screen input, etc.

[0053] Step S102, extract a model element corresponding to any model element type from the business requirement document through an identification model; wherein, the model element has corresponding element information.

[0054] Herein, the identification model is a large model.

[0055] Herein, the model element is a basic component for constructing a business model. The element information of the model element can be represented in a structured form, and its structured information (or element information) includes but is not limited to element name, element description content, element extraction location, etc. It should be noted that the present disclosure places no restrictions on the number of model elements extracted.

[0056] In the embodiments of the present disclosure, the business requirement document to be identified and the multiple model element types to be extracted are input into the identification model. The identification model identifies and extracts the model elements corresponding to any model element type in the business requirement document, thereby obtaining the model elements corresponding to the model element types.

[0057] It should be noted that the content of any paragraph in the business requirement document may simultaneously have the element information of the model elements under multiple model element types. Therefore, correspondingly, the model elements under multiple model element types can be extracted from the content of the relevant paragraphs in the business requirement document.

[0058] Exemplarily, taking the content of a certain paragraph in the business requirement document as an example for describing a business process, the model elements under the model element types of activity, task, step, and business entity, etc. can be extracted from the content of this paragraph.

[0059] Step S103: Construct the business model to be constructed according to the element information of each model element.

[0060] To improve the accuracy and reliability of business model construction, as a possible implementation, for the business model to be constructed, in response to the user's operation, based on the element information of each model element, determine the first target model element associated with the business model to be constructed from multiple model elements. Furthermore, construct the business model to be constructed according to the first target model element associated with the business model to be constructed. Among them, the user's operations include but are not limited to clicking, dragging and dropping, inputting, deleting, etc.

[0061] Specifically, the user reads and extracts the element information of each model element, analyzes the element information of each model element, and then selects the first target model element associated with the business model to be constructed from multiple model elements according to the business requirements. Thus, the execution entity of the present disclosure will, in response to the user's operation, obtain the first target model element associated with the business model to be constructed, and construct the business model to be constructed according to the first target model element associated with the business model to be constructed.

[0062] The modeling method of the embodiments of the present disclosure includes obtaining the business requirement document to be recognized and obtaining multiple model element types to be extracted; extracting the model elements corresponding to any model element type from the business requirement document through an identification model; where the model elements have corresponding element information; constructing the business model to be constructed according to the element information of each model element. Thus, the model elements in the business requirement document are quickly located and extracted through an automated identification model, solving the problem of low efficiency of manual identification, reducing the time for manual reading and parsing of documents, thereby accelerating the construction speed of the business model, improving the construction efficiency of the model, and since manual intervention is reduced, avoiding misunderstandings or omissions that may occur during manual extraction, and improving the accuracy of the model.

[0063] To clearly illustrate how to construct the business model to be constructed according to the element information of each model element in the above embodiments of the present disclosure, the present disclosure also proposes a modeling method.

[0064] Figure 2 It is a schematic flowchart of another modeling method provided by the embodiments of the present disclosure.

[0065] It should be noted that this modeling method can be executed alone, or can also be executed in combination with any one of the embodiments or possible implementation manners in the present disclosure, or can also be executed in combination with any one of the technical solutions in the related art. The embodiments of the present disclosure do not limit this.

[0066] Such as Figure 2As shown, the modeling method includes the following steps S201 to S206:

[0067] Step S201: Obtain the business requirement document to be recognized, and obtain multiple model element types to be extracted.

[0068] Step S202: Extract model elements corresponding to any model element type from the business requirement document through the recognition model.

[0069] It should be noted that the explanations of steps S201 to S202 can be referred to the relevant descriptions in any embodiment of the present disclosure, and will not be elaborated here.

[0070] Step S203: For any model element, determine whether to perform content optimization on the element information of the model element according to the data state of the model element.

[0071] Optionally, the data state of the model element includes a first state and a second state. Among them, the first state is, for example, a preset state, and the second state is, for example, an editing state.

[0072] In order to accurately determine whether to perform content optimization on the element information of the model element, as a possible implementation, for any model element, when the data state of the model element is the first state, it is determined to perform content optimization on the element information of the model element; while when the data state of the model element is the second state, it is determined not to perform content optimization on the element information of the model element. That is to say, for any model element, when the data state of the model element is the first state, it indicates that content optimization is required for the element information of the model element, and when the data state of the model element is the second state, it indicates that content optimization is not required for the element information of the model element. Thus, through the data state of the model element, a judgment basis is provided for the content optimization of the model element element information.

[0073] Step S204: In response to determining to perform content optimization on the element information of the model element, perform content optimization on the element information of the model element through the optimization model.

[0074] Among them, the optimization model is a large model. It should be explained that the optimization model can be the same as the recognition model, or it can also be different. The present disclosure does not limit this.

[0075] In the embodiment of the present disclosure, when it is determined to perform content optimization on the element information of the model element, the element information of the model element is input into the optimization model, so as to perform content optimization on the element information of the model element through the optimization model.

[0076] Exemplarily, the optimization model can be used to supplement the missing element description content, purpose, definition, scope, etc. in the element information of the model elements. Alternatively, the content can also be optimized and improved based on the existing element information of the model elements. By using the optimization model to improve or adjust the element information of the model elements, the purpose of optimization can be achieved, the data quality of the model elements used to build the business model can be improved, and the stability and reliability of the subsequently built business model can be enhanced.

[0077] Step S205, in response to determining not to perform content optimization on the element information of the model element, send a first prompt message to the user to prompt the user to confirm the element information of the model element.

[0078] In the embodiments of the present disclosure, when it is determined not to perform content optimization on the element information of the model element, a prompt message can be sent to the user at this time to prompt the user to confirm the element information of the model element. Thereby, the transparency of the information is improved, enabling the user to more clearly understand the element information of the model element and correct the information in a timely manner when the information is incorrect, enhancing the accuracy and reliability of the subsequently built business model, and enhancing the user's sense of participation and trust in the element information management.

[0079] It should be noted that for any model element, step S204 and step S205 are executed alternatively.

[0080] Step S206, based on the element information of each optimized model element and / or the element information of each information-confirmed model element, construct the business model to be constructed.

[0081] As an example, based on the element information of each optimized model element, construct the business model to be constructed.

[0082] As another example, based on the element information of each information-confirmed model element, construct the business model to be constructed.

[0083] As still another example, based on the element information of each optimized model element and the element information of each information-confirmed model element, construct the business model to be constructed.

[0084] To implement the construction of the business model to be constructed, as a possible implementation manner, in response to the user's operation, based on the element information of each optimized model element and / or the element information of each information-confirmed model element, determine the second target model element associated with the business model to be constructed from each model element. Furthermore, according to the second target model element associated with the business model to be constructed, construct the business model to be constructed. Among them, the user's operation includes but is not limited to clicking, dragging and dropping, inputting, deleting, etc.

[0085] Specifically, the user reads and analyzes the element information of each optimized model element and / or the element information of each model element after information confirmation, and then, according to business requirements, selects a second target model element associated with the business model to be constructed from multiple model elements. Thus, the execution subject of the present disclosure will, in response to the user's operation, obtain the second target model element associated with the business model to be constructed, and construct the business model to be constructed according to the second target model element associated with the business model to be constructed.

[0086] In the modeling method of the embodiments of the present disclosure, for any model element, it is determined whether to perform content optimization on the element information of the model element according to the data state of the model element; in response to determining to perform content optimization on the element information of the model element, the content of the element information of the model element is optimized through an optimization model; in response to determining not to perform content optimization on the element information of the model element, a first prompt message is sent to the user to prompt the user to perform information confirmation on the element information of the model element; a business model to be constructed is constructed based on the element information of each optimized model element and / or the element information of each model element after information confirmation. Thus, by performing content optimization on the element information of the model element, the data accuracy, integrity, consistency, etc. of the model element can be improved, the data quality of the model element can be enhanced, and further the reliability of the constructed business model can be improved. At the same time, through the optimization model, the automatic optimization of the element information of the model element is realized, manual intervention is reduced, errors caused by human factors are reduced, and work efficiency is improved; by manually performing information confirmation on the element information of the model element, the user experience is enhanced, and the data accuracy of the model element is further improved.

[0087] As a possible implementation manner, in the case where the data state of the model element includes a first state and a second state, in order to clearly illustrate how the first state of the model element in the above embodiments of the present disclosure is obtained, the present disclosure also proposes a modeling method.

[0088] Figure 3 It is a schematic flowchart of another modeling method provided by the embodiments of the present disclosure.

[0089] It should be noted that this modeling method can be executed alone, or can be executed in combination with any one of the embodiments or possible implementation manners in the present disclosure, or can also be executed in combination with any one of the technical solutions in the related art. The embodiments of the present disclosure do not limit this.

[0090] As Figure 3 shown, this modeling method includes the following steps S301 to S308:

[0091] Step S301, obtain a business requirement document to be recognized and obtain multiple model element types to be extracted.

[0092] Step S302: Extract model elements corresponding to any model element type from the business requirement document through an identification model, where the model elements have corresponding element information.

[0093] It should be noted that the explanations of steps S301 to S302 can be referred to the relevant descriptions in any embodiment of the present disclosure, and will not be elaborated here.

[0094] In the embodiments of the present disclosure, after extracting model elements corresponding to any model element type from the business requirement document through the identification model, the data status of each model element can be marked as the first status. Exemplarily, the data status of each model element can be marked as the default data status, that is, the preset status.

[0095] Step S303: For any model element, determine whether there is historical data in the target database that has a data conflict with the model element.

[0096] Among them, data conflicts include but are not limited to naming conflicts, data value conflicts, entity identifier conflicts, value range conflicts, data representation conflicts, data unit conflicts, data precision re-reading, data credibility conflicts, etc.

[0097] Among them, the target database is used to store model elements, business models, etc.

[0098] In the embodiments of the present disclosure, for any model element, it can be determined whether there is historical data in the target database that has a data conflict with the model element.

[0099] In order to effectively and accurately determine whether there are data elements in the target database that have a data conflict with the model element, as a possible implementation, for any model element, extract the keywords in the element information of the model element, and query the target database based on the keywords to obtain the corresponding historical data; compare the element information of the model element with the queried historical data to determine whether there is historical data in the target database that has a data conflict with the model element.

[0100] As an example, for any model element, the element name in the element information of the model element can be extracted as the keyword, and the target database can be queried based on the keyword to obtain the corresponding historical data; compare the element name of the model element with the element name in the queried historical data. When the element name of the model element is the same as the element name in the queried historical data, it is determined that there is historical data in the target database that has a data conflict with the model element.

[0101] As another example, for any model element, the element name in the element information of the model element can be extracted as a keyword, and the target database can be queried based on this keyword to obtain the corresponding historical data; the value range of the model element is compared with the value range in the queried historical data. When the value range of the model element is the same as the value range in the queried historical data, it is determined that there is historical data in the target database that has a data conflict with the model element.

[0102] And so on, which will not be elaborated here.

[0103] It should be noted that only the element name is used as an example for the keyword in the above example. In actual applications, the keyword can also be a unique identifier, code, creation timestamp, path, version, etc., and the present disclosure does not limit this.

[0104] Step S304, in response to the existence of historical data in the target database that has a data conflict with the model element, according to the pre-set conflict handling rules, perform conflict handling on the element information of the model element, and set the data status of the model element to the first status after the conflict handling.

[0105] Among them, the conflict handling rules are pre-set and are used to indicate the processing methods or measures to be taken for the element information of the model element with data conflicts.

[0106] In the embodiments of the present disclosure, when there is historical data in the target database that has a data conflict with the model element, according to the pre-set conflict handling rules, conflict handling is performed on the element information of the model element. Thus, through the conflict handling rules, the data conflict problem of the model element can be intelligently and effectively solved, and the data accuracy, integrity, and consistency of the model element can be improved.

[0107] In a possible implementation manner of the present disclosure, when there is historical data in the target database that has a data conflict with the model element, the element information of the model element can also be adjusted manually and / or the historical data in the target database that has a data conflict with the model element, so as to perform conflict handling on the element information of the model element.

[0108] It can be understood that after the conflict handling, the element information of the model element may not yet meet the review standard. Therefore, in the embodiments of the present disclosure, the data status of the model element can be set to the first status after the conflict handling. For example, the data status of the model element is changed from the second status to the first status, so as to facilitate subsequent determination of whether to perform content optimization on the element information of the model element based on the data status of the model element.

[0109] Step S305, for any model element, determine whether to perform content optimization on the element information of the model element according to the data status of the model element.

[0110] Wherein, when the data status of the model element is the first status, it is determined to perform content optimization on the element information of the model element; while when the data status of the model element is the second status, it is determined not to perform content optimization on the element information of the model element.

[0111] Step S306, in response to determining to perform content optimization on the element information of the model element, perform content optimization on the element information of the model element through an optimization model.

[0112] Step S307, in response to determining not to perform content optimization on the element information of the model element, send a first prompt message to the user to prompt the user to confirm the element information of the model element.

[0113] Step S308, based on the element information of each optimized model element and / or the element information of each information-confirmed model element, construct a business model to be constructed.

[0114] It should be noted that the explanatory descriptions of steps S305 to S308 can be referred to the relevant descriptions in any embodiment of the present disclosure, and will not be elaborated here.

[0115] The modeling method of the embodiment of the present disclosure determines whether there is historical data in the target database that has a data conflict with the model element for any model element; in response to the existence of historical data in the target database that has a data conflict with the model element, according to the pre-set conflict handling rules, perform conflict handling on the element information of the model element, and set the data status of the model element to the first status after the conflict handling. Thus, by checking whether there is historical data in the target database that conflicts with the model element, the problem of data inconsistency can be discovered and solved in a timely manner, and the overall consistency of the data can be maintained; furthermore, based on the pre-set conflict handling rules, the problem of data conflict is automatically solved, reducing the need for manual access, improving the processing efficiency and accuracy; finally, the timely setting of the data status after the conflict handling helps to track and manage the data status of the model element, ensuring the accuracy and traceability of the data status.

[0116] As another possible implementation, in the case where the data status of the model element includes the first status and the second status, in order to clearly illustrate how the first status of the model element in the embodiment of the present disclosure is obtained, the present disclosure also proposes a modeling method.

[0117] Figure 4 It is a schematic flowchart of another modeling method provided by the embodiment of the present disclosure.

[0118] It should be noted that this modeling method can be executed alone, or it can be executed in combination with any one of the embodiments in the present disclosure or the possible implementation manners in the embodiments, or it can also be executed in combination with any one of the technical solutions in the related art. The embodiments of the present disclosure do not limit this.

[0119] As Figure 4 shown, this modeling method includes the following steps S401 to S408:

[0120] Step S401, obtain the business requirement document to be recognized, and obtain multiple model element types to be extracted.

[0121] Step S402, extract the model elements corresponding to any model element type from the business requirement document through the recognition model, where the model elements have corresponding element information.

[0122] It should be noted that for the explanations of steps S401 to S402, reference can be made to the relevant descriptions in any embodiment of the present disclosure, and details are not elaborated here.

[0123] In the embodiments of the present disclosure, after extracting the model elements corresponding to any model element type from the business requirement document through the recognition model, the data status of each model element can be marked as the first status. Exemplarily, the data status of each model element can be marked as the default data status, that is, the preset status.

[0124] Step S403, for any model element, determine whether there is information missing in the element information of the model element.

[0125] It can be understood that there may be a situation where the element information of the structured model element is missing.

[0126] As an example, assume that the structured information of the model element, that is, the element information is shown in Table 1:

[0127] Table 1 Element Information of Model Elements

[0128]

[0129] As shown in Table 1, for the model element with the element name of querying product information, there is a situation where supplementary information is missing, and for the model element with the element name of customer information, there is a situation where the element description information is missing.

[0130] In the embodiments of the present disclosure, for any model element, the fields with empty element information of the model element can be recognized. Thus, when there are fields with empty element information in the element information of the model element, it indicates that there is information missing in the element information of the model element, otherwise, there is no information missing.

[0131] Step S404, in response to the lack of element information of the model element, send a second prompt message to the user to prompt the user to supplement the element information of the model element, and set the data status of the model element to the first status after the information is supplemented.

[0132] In the embodiments of the present disclosure, when there is a lack of element information of the model element, a prompt message can be sent to the user to prompt the user to supplement the element information of the model element. Thus, through information supplementation, the data integrity, accuracy, and consistency of the model element are improved.

[0133] It can be understood that after the information is supplemented, the element information of the model element may not yet meet the review criteria. Therefore, in the embodiments of the present disclosure, the data status of the model element can be set to the first status after the information is supplemented. For example, the data status of the model element is changed from the second status to the first status, so as to facilitate subsequent determination of whether to perform content optimization on the element information of the model element based on the data status of the model element.

[0134] Step S405, for any model element, determine whether to perform content optimization on the element information of the model element according to the data status of the model element.

[0135] Wherein, when the data status of the model element is the first status, it is determined to perform content optimization on the element information of the model element; while when the data status of the model element is the second status, it is determined not to perform content optimization on the element information of the model element.

[0136] Step S406, in response to determining to perform content optimization on the element information of the model element, perform content optimization on the element information of the model element through an optimization model.

[0137] Step S407, in response to determining not to perform content optimization on the element information of the model element, send a first prompt message to the user to prompt the user to confirm the element information of the model element.

[0138] Step S408, based on the element information of each optimized model element and / or the element information of each information-confirmed model element, construct a business model to be constructed.

[0139] It should be noted that the explanations of steps S405 to S408 can refer to the relevant descriptions in any embodiment of the present disclosure, and will not be elaborated here.

[0140] In some scenarios (such as the scenario of information confirmation, etc.), in order to assist the user in quickly locating the position of the model element in the business requirement document, so as to help the user better understand the model element, in a possible implementation manner of the embodiments of the present disclosure, when the element information of each model element includes the element extraction position, for any model element, the model element is displayed at the element extraction position corresponding to the model element in the business requirement document in a preset enhancement manner. Wherein, the preset enhancement manner includes but is not limited to font size adjustment, font adjustment, font style adjustment, font color adjustment, character spacing adjustment, line adjustment, special effect addition, inserting a text box, etc.

[0141] The modeling method of the embodiments of the present disclosure determines whether there is missing information in the element information of any model element; in response to the existence of missing information in the element information of the model element, a second prompt message is sent to the user to prompt the user to supplement the information of the model element, and the data status of the model element is set to the first status after the information is supplemented. Thus, by checking whether there is missing information in the element information of the model element, the problem of missing information can be discovered and solved in time, and the integrity of the data can be maintained; furthermore, when missing information is detected, manual information supplementation is performed to improve the overall quality of the data and reduce errors caused by incomplete data; finally, the timely setting of the data status after information supplementation helps to track and manage the data status of the model element, ensuring the accuracy and traceability of the data status.

[0142] When the element information of the model element includes the element name, in order to clearly illustrate how to obtain the element name of the model element in any of the above embodiments of the present disclosure, the present disclosure also proposes a modeling method.

[0143] Figure 5 It is a schematic flowchart of another modeling method provided by the embodiments of the present disclosure.

[0144] It should be noted that this modeling method can be executed alone, or it can also be executed in combination with any one of the embodiments in the present disclosure or the possible implementation manners in the embodiments, or it can also be executed in combination with any one of the technical solutions in the related technologies. The embodiments of the present disclosure do not limit this.

[0145] As Figure 5 shown, this modeling method includes the following steps S501 to S505:

[0146] Step S501, obtain the business requirement document to be recognized, and obtain multiple model element types to be extracted.

[0147] Step S502: Extract model elements corresponding to any model element type from the business requirements document through an identification model; wherein, the model elements have corresponding element information.

[0148] It should be noted that the explanations of steps S501 to S502 can be referred to the relevant descriptions in any embodiment of the present disclosure, and will not be elaborated here.

[0149] Step S503: For any model element, use the target model to name the initial element name of the model element in multiple naming styles to obtain multiple candidate names of the model element.

[0150] Among them, the target model is a large model. It should be noted that the target model can be the same as the identification model, or it can also be different. The present disclosure does not limit this.

[0151] Among them, the naming styles include but are not limited to corresponding styles such as CamelCase, PascalCase, snake_case, lowercase letter with dot naming method, uppercase letter with dot naming method, etc.

[0152] In the embodiment of the present disclosure, when the model elements are extracted, the element name in the element information of the model elements at this time can be determined as the initial element name. Furthermore, the target model can be used to name the initial element name of the model elements in multiple naming styles, so as to obtain multiple candidate names of the model elements.

[0153] Step S504: Determine the target element name of the model element from the multiple candidate names of the model element.

[0154] In order to accurately determine the element name of the model element, as a possible implementation manner, at least one target candidate name without naming conflicts is screened out from the multiple candidate names of the model element. Furthermore, any target candidate name can be determined as the target element name of the model element, or the target candidate name selected by the user among at least one target candidate name can be determined as the target element name of the model element.

[0155] In order to implement the screening of the target candidate names, as a possible implementation manner, for any candidate name, query the first database according to the candidate name to determine whether there is historical data matching the candidate name in the first database. When there is no historical data matching the candidate name in the first database, then determine that candidate name as the target candidate name.

[0156] Among them, the first database can be used to store model elements, business models, etc.

[0157] In order to more effectively manage and maintain the element information of the extracted model elements, in a possible implementation manner of the embodiments of the present disclosure, in response to a user operation, a target element type is determined from multiple model element types, so that the element information of the model elements corresponding to the target element type among multiple model elements can be displayed. Thus, it is convenient for the user to quickly locate and view the model element information related to the target element type according to actual needs, so as to provide targeted management or maintenance measures, improve the flexibility of model element management, and enhance the user experience.

[0158] Step S505: Construct a business model to be constructed according to the element information of each model element.

[0159] Among them, the element information of any model element may include a target element name.

[0160] It should be noted that the explanation of step S505 can be referred to the relevant description in any embodiment of the present disclosure, and will not be elaborated here.

[0161] In the modeling method of the embodiments of the present disclosure, the initial element names of model elements are named in multiple naming styles by using a target model to obtain multiple candidate names of the model elements; the target element name of the model element is determined from the multiple candidate names of the model elements. Thus, multiple candidate names of model elements are automatically generated by the target model, providing more choices for users and helping to meet naming preferences in different scenarios.

[0162] The above embodiments are the construction methods of the business model, that is, the modeling methods. The following is the application method of the business model.

[0163] Figure 6 It is a schematic flowchart of a question-and-answer method provided by the embodiments of the present disclosure.

[0164] As Figure 6 shown, the question-and-answer method includes the following steps S601 to S602:

[0165] Step S601: Obtain a business question.

[0166] Among them, a business question is a question generated based on business requirements. Business requirements are specific conditions, functions, and limitations that need to be met in order to achieve the business strategic goals of relevant enterprises or organizations, or to improve the operational efficiency of relevant enterprises or organizations, etc.

[0167] Exemplarily, business questions can be generated based on multiple aspects such as business process optimization, cost-benefit analysis, and market trend prediction.

[0168] In order to effectively obtain business questions, as a possible way, a business question can be obtained through manual input operations.

[0169] As another possible implementation, obtain a target file containing business problems, and identify the business problems in the target file to obtain the business problems.

[0170] Step S602: Generate an answer to the business problem based on the business model constructed by the modeling method.

[0171] It should be noted that the present disclosure does not limit the number of business models constructed by the modeling method.

[0172] To improve the accuracy of the generated answer, as a possible implementation, identify and extract the third target model element in the business problem through the identification model, query the business model constructed by the modeling method according to the element name of the third target model element, so as to obtain the target business model related to the third target model element from the business model constructed by the modeling method, and then generate an answer to the target problem according to the target business model. Among them, the identification model is a large model.

[0173] The question-and-answer method of the embodiments of the present disclosure obtains business problems; and generates answers to the business problems based on the business models constructed by the modeling method. Thus, the problem can be accurately located, and corresponding answers can be quickly generated based on the constructed business models, providing strong support for decision-making.

[0174] To clearly illustrate the modeling method and the question-and-answer method of the present disclosure, the following will be described in detail with examples.

[0175] As an example, it is described that both the modeling method and the question-and-answer method are applied to a business modeling platform. Among them, as Figure 7 shown, the process of the modeling method includes:

[0176] Step 1: Manually upload a business requirements document to the business modeling platform. The business modeling platform identifies the document content of the business requirements document. At the same time, the business modeling platform obtains multiple element categories to be extracted (denoted as model element types in the present disclosure). Then, the business modeling platform sends the identified business requirements document and the obtained element categories to an AI (Artificial Intelligence) business modeling large model (denoted as the identification model in the present disclosure) to identify and extract the model elements corresponding to any element category in the business requirements document through the AI business modeling large model.

[0177] Among them, the document formats of business requirements documents that the business modeling platform can support for uploading and identifying include DOC format, PDF format, etc.

[0178] Among them, the business modeling platform can support multiple selections of element categories to be extracted, and the element categories include but are not limited to activities, tasks, steps, basic products, product conditions, business entities, entity relationships, etc.

[0179] Optionally, the business modeling platform can support checking element categories from multiple preset element types, so as to extract model elements corresponding to the element categories in a targeted manner through the AI business modeling large model, and support multiple selections.

[0180] It should be noted that the element information of model elements under multiple element categories may exist simultaneously in the content of any paragraph in the business requirements document. Therefore, correspondingly, model elements under multiple element categories can be extracted from the content of relevant paragraphs in the business requirements document.

[0181] It should also be noted that after the AI business modeling large model identifies and extracts model elements, the AI business modeling large model returns the extracted model elements to the business modeling platform in a structured form. Among them, the element information of the returned model elements includes but is not limited to element names, element description contents, element extraction positions, etc.

[0182] Optionally, the AI business modeling large model can name the element names of the extracted model elements in multiple naming styles.

[0183] Step 2: The business modeling platform receives the model elements extracted by the AI business modeling large model and can display the extracted model elements on the display interface of the business modeling platform.

[0184] As a possible implementation method, the business modeling platform can classify and display the extracted model elements according to element categories.

[0185] As another possible implementation method, the business modeling platform determines a target element type from multiple element categories in response to a user's operation, and displays the element information of the model elements corresponding to the target element type among multiple model elements.

[0186] As yet another possible implementation method, for any model element, the model element is displayed at the element extraction position corresponding to the model element in the business requirements document in a preset enhanced manner. It should be noted that the element information of model elements under multiple element categories may exist simultaneously in the content of any paragraph in the business requirements document, and the element information of multiple model elements under the same element category may also exist, and so on.

[0187] Step 3: The business modeling platform sets the data status of the extracted model elements to the default status, i.e., the preset status (denoted as the second status in this disclosure), and matches the element information of the extracted model elements with the historical data in the asset library (denoted as the target database in this disclosure) to check whether there is historical data in the asset library that conflicts with the element information of the model elements; if there is historical data in the asset library that conflicts with the element information of the model elements, the conflict handling of the element information of the model elements can be performed through manual processing methods.

[0188] Step 5: The business modeling platform loads the element information of the model elements after conflict handling, and updates the data status of the model elements after conflict handling from the preset status to the editing status (denoted as the first status in this disclosure).

[0189] Optionally, the model elements with the preset data status can be displayed at the top.

[0190] Step 6: Identify the data status of the model elements and provide targeted prompts.

[0191] When it is recognized that there are model elements with the preset data status among the model elements, a prompt message can be sent to the user to prompt the user to confirm the element information of the model elements with the preset data status;

[0192] When it is recognized that there are model elements with missing information among the model elements, a prompt message can be sent to the user to prompt the user to supplement (or improve) the information of the model elements with missing information, and after the information is supplemented, the data status of the model element is set to the editing status;

[0193] When it is recognized that there are model elements with the editing data status among the model elements, the element information of the model elements with the editing data status can be sent to the AI business modeling large model in a structured form, so that the AI business modeling large model can perform content optimization on the element information of the model elements with the editing data status, for example, it can automatically supplement the description, purpose, definition, scope, etc. of the model elements, or perform content optimization and improvement based on the existing content.

[0194] Optionally, after the user confirms the element information of the model elements optimized by the AI business modeling large model, it is loaded into the business modeling platform by field.

[0195] Step 7: The business modeling platform responds to the user's operation and constructs the business model to be constructed according to the element information of each model element.

[0196] It should be noted that the business modeling platform can store the constructed business model in the relevant database.

[0197] Therefore, based on the above modeling method, the question-and-answer method includes the following steps:

[0198] Obtain a business question and generate an answer to the business question based on the business model constructed according to the above modeling method.

[0199] In summary, the modeling method of the present disclosure has the following advantages:

[0200] 1. It can quickly and directionally identify and extract model elements corresponding to element categories;

[0201] 2. The extracted model elements can be located and traced in the business requirement document;

[0202] 3. By comparing new and old data, it is possible to verify whether there are data conflicts in the extracted model elements, and conflicts in the model elements with data conflicts can be processed in a timely manner to improve data accuracy;

[0203] 4. By optimizing content or supplementing information, the integrity, accuracy, and consistency of the element information of the model elements are improved;

[0204] 5. It supports naming model elements in different styles, provides more choices for users, helps to meet naming preferences in different scenarios, is flexible, and improves the user experience.

[0205] To implement the embodiments of the above modeling method, the present disclosure also provides a modeling device.

[0206] Figure 8 It is a schematic structural diagram of a modeling device provided by an embodiment of the present disclosure.

[0207] As Figure 8 shown, the modeling device 800 includes: an acquisition module 801, an extraction module 802, and a construction module 803.

[0208] Among them, the acquisition module 801 is configured to acquire a business requirement document to be recognized and acquire multiple model element types to be extracted.

[0209] The extraction module 802 is configured to extract model elements corresponding to any model element type from the business requirement document by identifying the model; among them, the model elements have corresponding element information.

[0210] The construction module 803 is configured to construct a business model to be constructed according to the element information of each model element.

[0211] In a possible implementation manner of the embodiments of the present disclosure, the construction module 803 is configured to: for any model element, determine whether to perform content optimization on the element information of the model element according to the data status of the model element; in response to determining to perform content optimization on the element information of the model element, perform content optimization on the element information of the model element through an optimization model; in response to determining not to perform content optimization on the element information of the model element, send a first prompt message to the user to prompt the user to confirm the information of the model element; and construct a business model to be constructed based on the element information of each optimized model element and / or the element information of each information-confirmed model element.

[0212] In a possible implementation manner of the embodiments of the present disclosure, the data status includes a first status and a second status; the construction module 803 is configured to: in response to the data status of the model element being the first status, determine to perform content optimization on the element information of the model element; in response to the data status of the model element being the second status, determine not to perform content optimization on the element information of the model element.

[0213] In a possible implementation manner of the embodiments of the present disclosure, the modeling device 800 further includes:

[0214] A first determination module, configured to determine whether there is historical data in the target database that has a data conflict with any model element.

[0215] A first processing module, configured to, in response to there being historical data in the target database that has a data conflict with the model element, perform conflict processing on the element information of the model element according to a pre-set conflict processing rule, and set the data status of the model element to the first status after the conflict processing.

[0216] In a possible implementation manner of the embodiments of the present disclosure, the modeling device 800 further includes:

[0217] A second determination module, configured to determine whether there is information missing in the element information of any model element.

[0218] A second processing module, configured to, in response to there being information missing in the element information of the model element, send a second prompt message to the user to prompt the user to supplement the information of the model element, and set the data status of the model element to the first status after the information supplement.

[0219] In a possible implementation manner of the embodiments of the present disclosure, the element information of the model element includes an element name; the modeling device 800 further includes:

[0220] A naming module is used to name the initial element name of a model element in multiple naming styles using a target model for any model element, obtaining multiple candidate names for the model element.

[0221] A third determination module is used to determine the target element name of the model element from multiple candidate names of the model element.

[0222] In a possible implementation manner of the embodiments of the present disclosure, the obtaining module 801 is used to: read and display multiple preset element types in an element type library; and determine multiple model element types from the multiple preset element types in response to a user's selection operation.

[0223] In a possible implementation manner of the embodiments of the present disclosure, the modeling device 800 further includes:

[0224] A fourth determination module is used to determine a target element type from multiple model element types in response to a user's selection operation.

[0225] A display module is used to display the element information of the model elements corresponding to the target element type among multiple model elements.

[0226] In a possible implementation manner of the embodiments of the present disclosure, the element information of each model element includes an element extraction position, and the modeling device 800 further includes:

[0227] A display module is used to display any model element at the element extraction position corresponding to the model element in a business requirement document in a preset enhanced manner.

[0228] It should be noted here that the modeling device provided in the embodiments of the present disclosure can implement all the method steps implemented in the above Figures 1 to 5 method embodiments and can achieve the same technical effects. The same parts and beneficial effects as those in the method embodiments are not specifically described in this embodiment again.

[0229] To implement the embodiments of the above question-and-answer method, the present disclosure also provides a question-and-answer device.

[0230] Figure 9 It is a schematic structural diagram of a question-and-answer device provided in the embodiments of the present disclosure.

[0231] As Figure 9 shown, the question-and-answer device 900 includes: an obtaining module 901 and a generating module 902.

[0232] Among them, the obtaining module 901 is used to obtain a business question.

[0233] A generation module 902, configured to generate an answer to a business problem based on a business model constructed by the modeling method proposed in the embodiment of the first aspect of the present disclosure.

[0234] It should be noted here that the question-and-answer device provided in the embodiment of the present disclosure can implement all the method steps implemented by the above Figure 6 method embodiment, and can achieve the same technical effects. Therefore, the same parts and beneficial effects as those in the method embodiment will not be specifically described in this embodiment.

[0235] To implement the above embodiments, the present disclosure also proposes an electronic device. The electronic device can be any device with computing capabilities and includes: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the modeling method proposed in the embodiment of the first aspect of the present disclosure or the question-and-answer method proposed in the embodiment of the second aspect of the present disclosure is implemented.

[0236] As an example, Figure 10 FIG. 13 is a schematic structural diagram of an electronic device 1000 shown in an exemplary embodiment of the present disclosure. As Figure 10 shown, the above-mentioned electronic device 1000 may further include:

[0237] A memory 1010 and a processor 1020, and a bus 1030 connecting different components (including the memory 1010 and the processor 1020). The memory 1010 stores a computer program, and when the processor 1020 executes the program, the modeling method described in the embodiment of the present disclosure is implemented.

[0238] The bus 1030 represents one or more of several types of bus structures, including a memory bus or a memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any bus structure in a variety of bus structures. For example, these architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

[0239] The electronic device 1000 typically includes a variety of electronic device-readable media. These media can be any available media accessible by the electronic device 1000, including volatile and non-volatile media, removable and non-removable media.

[0240] The memory 1010 may also include computer system readable media in the form of volatile memory, such as random access memory (RAM) 1040 and / or cache memory 1050. The server 1000 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 1060 can be used for reading and writing on non-removable, non-volatile magnetic media ( Figure 10 not shown, commonly referred to as a "hard disk drive"). Although Figure 10 not shown in the figure, a disk drive for reading and writing on removable non-volatile disks (such as "floppy disks"), and an optical disk drive for reading and writing on removable non-volatile optical disks (such as CD-ROM, DVD-ROM or other optical media) may be provided. In these cases, each drive may be connected to the bus 1030 through one or more data media interfaces. The memory 1010 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present disclosure.

[0241] A program / utilities 1080 having a set (at least one) of program modules 1070 may be stored, for example, in the memory 1010. Such program modules 1070 include - but are not limited to - an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. The program modules 1070 generally perform the functions and / or methods in the embodiments described in the present disclosure.

[0242] The electronic device 1000 may also communicate with one or more external devices 1090 (such as a keyboard, a pointing device, a display 1091, etc.), and may also communicate with one or more devices that enable a user to interact with the electronic device 1000, and / or communicate with any device that enables the electronic device 1000 to communicate with one or more other computing devices (such as a network card, a modem, etc.). Such communication may be through an input / output (I / O) interface 1092. Moreover, the electronic device 1000 may also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 1093. As shown in the figure, the network adapter 1093 communicates with other modules of the electronic device 1000 through the bus 1030. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 1000, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0243] The processor 1020 executes various functional applications and data processing by running programs stored in the memory 1010.

[0244] It should be noted that for the implementation process and technical principle of the electronic device in this embodiment, refer to the foregoing explanation of the modeling method of the embodiments of the present disclosure, which will not be elaborated here.

[0245] To implement the above embodiments, the present disclosure also proposes a non-transitory computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the modeling method or the question-and-answer method proposed in any of the foregoing embodiments of the present disclosure.

[0246] To implement the above embodiments, the present disclosure also proposes a computer program product. When the instructions in the computer program product are executed by a processor, they execute the modeling method or the question-and-answer method proposed in any of the foregoing embodiments of the present disclosure.

[0247] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0248] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0249] Any process or method description shown in the flowchart or described in other ways herein can be understood as representing a module, segment, or part of code including one or more executable instructions for implementing a customized logical function or process. The scope of the preferred embodiments of the present disclosure includes additional implementations, where the functions may be executed in a substantially simultaneous manner or in an opposite order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art of the embodiments of the present disclosure.

[0250] The logic and / or steps represented in the flowchart or otherwise described herein can, for example, be considered as a definable sequence list of executable instructions for implementing logical functions, which can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or used in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in combination with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other appropriate processing as necessary, and then storing it in a computer memory.

[0251] It should be understood that the various parts of the present disclosure can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0252] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the method of the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0253] In addition, in each embodiment of the present disclosure, each functional unit can be integrated into one processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0254] The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present disclosure have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present disclosure.

Claims

1. A modeling method, characterized in that: The method comprises: Obtain a business requirement document to be identified, and obtain multiple model element types to be extracted; Extracting a model element corresponding to any of the model element types from the business requirement document by identifying a model; wherein the model element has corresponding element information; A business model to be constructed is constructed according to the element information of each of the model elements.

2. The method according to claim 1, characterized in that The step of constructing the business model to be constructed according to the element information of each of the model elements includes: For any of the model elements, determining whether to perform content optimization on the element information of the model element according to the data state of the model element; In response to determining to perform content optimization on the element information of the model element, performing content optimization on the element information of the model element by optimizing the model; In response to determining that content optimization is not performed on the element information of the model element, sending first prompt information to the user to prompt the user to confirm the element information of the model element; Based on the element information of each optimized model element and / or the element information of each model element after confirmation, a business model to be constructed is constructed.

3. The method according to claim 2, characterized in that The data state includes a first state and a second state; and determining whether to perform content optimization on the element information of the model element according to the data state of the model element includes: In response to the data state of the model element being the first state, determining to perform content optimization on the element information of the model element; In response to the data state of the model element being the second state, it is determined not to perform content optimization on the element information of the model element.

4. The method according to claim 3, characterized in that Before constructing the business model to be constructed according to the element information of each of the model elements, the method further includes: For any of the model elements, determining whether there is historical data in the target database that has data conflict with the model element; In response to the existence of historical data in the target database that has data conflicts with the model element, conflict processing is performed on the element information of the model element according to a preset conflict processing rule, and the data state of the model element is set to the first state after the conflict processing.

5. The method according to claim 3, characterized in that: Before constructing the business model to be constructed according to the element information of each of the model elements, the method further includes: For any of the model elements, determining whether element information of the model element has any missing information; In response to missing information in the element information of the model element, second prompt information is sent to the user to prompt the user to supplement the element information of the model element, and after the information is supplemented, the data state of the model element is set to the first state.

6. The method according to any one of claims 1 to 5, characterized in that: The element information of the model element includes an element name; after extracting a model element corresponding to any model element type from the business requirement document by identifying the model, the method further includes: For any of the model elements, the target model is used to name the initial element name of the model element in multiple naming styles to obtain multiple candidate names of the model element; A target element name of the model element is determined from a plurality of candidate names of the model element.

7. The method according to any one of claims 1 to 5, characterized in that: The obtaining of multiple model element types to be extracted includes: Read and display multiple preset element types in the element type library; In response to a selection operation of a user, the plurality of model element types are determined from the plurality of preset element types.

8. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: In response to a selection operation by a user, determining a target element type from the plurality of model element types; The element information of the model elements corresponding to the target element type among the plurality of the model elements is displayed.

9. The method according to any one of claims 1 to 5, characterized in that: The element information of each of the model elements includes an element extraction position, and the method further includes: For any of the model elements, the model element is displayed in a preset enhanced manner at an element extraction position corresponding to the model element in the business requirement document.

10. A question-answering method, characterized in that: The method comprises: Get business problems; The answer to the business question is generated based on the business model constructed by the method according to any one of claims 1 to 9.

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