Question system construction method and device, equipment, storage medium and program product
By using a full-process data inquiry system construction method, business and data requirements information is obtained, service interface designs and knowledge base import information are generated, and the data is combined according to the calling order. This solves the problem of long implementation cycles of existing tools and achieves efficient implementation of the data inquiry system.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-23
- Publication Date
- 2026-03-31
AI Technical Summary
Existing conversational business intelligence tools suffer from long implementation cycles and low efficiency, mainly due to limitations in specific technical implementations during the system development phase, resulting in a fragmented and inconsistent implementation process.
This paper provides a method for building a data query system that covers the entire process of data. By acquiring business requirements and data requirements, it generates service interface design information and knowledge base import information, and combines them according to the call order to ensure implementation consistency and predictability, avoiding on-the-fly modifications.
It shortened the implementation cycle of the data collection system, improved implementation efficiency, ensured the standardization and predictability of the implementation process, avoided duplication of work and rework, and improved implementation quality.
Smart Images
Figure CN121764554A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of big data processing technology, and in particular to a method, apparatus, device, computer-readable storage medium, and computer program product for constructing a data processing system. Background Technology
[0002] In the current wave of enterprise digital transformation, conversational business intelligence tools are gradually becoming a key technology for improving decision-making efficiency because they allow users to conveniently query and analyze data using natural language. The realization of its core function, "intelligent data querying," relies on the effective scheduling of heterogeneous backend data services and a precise understanding of domain knowledge.
[0003] However, existing implementation processes for conversational Business Intelligence (BI) tools have significant shortcomings. Current industry practices and related technical solutions primarily focus on specific technical implementations during the system development phase, such as training natural language processing models, parsing and translating query statements, and front-end and back-end interaction design. This limitation leads to numerous challenges for enterprises when introducing and implementing such tools. For example, the implementation of intelligent query systems often falls into a "make-as-you-go" dilemma, resulting in unreasonably prolonged implementation cycles and low efficiency. Summary of the Invention
[0004] This application provides a method, apparatus, device, computer-readable storage medium, and computer program product for constructing a data collection system, which can shorten the implementation cycle of the data collection system and improve efficiency.
[0005] In a first aspect, embodiments of this application provide a method for constructing a question-and-answer system, including: Obtain business requirement information and corresponding data requirement information. The data requirement information includes service interface modification requirements and import template information for fields in the knowledge base. Based on the data requirements, generate service interface design information and knowledge base import information. The service interface design information includes the design information for the input parameters of the data service interface, the output parameters of the data service interface, entity extraction prompts, and the output parameters of the entity extraction plugin service interface. Based on business requirements, generate the calling order of the data service interface and the entity extraction plugin service interface; According to the order of invocation, the program information corresponding to the service interface design information and the knowledge base import information are combined to obtain the first question system.
[0006] In one possible implementation, the business requirement information includes functional requirement information and scenario requirement information; obtaining the data requirement information corresponding to the business requirement information includes: Use the internal data service interface of the initial question system to obtain the initial output parameters of the initial question system; If the initial output parameters cannot meet the functional and scenario requirements, generate service interface modification requirements for the internal data service interface. Obtain external data service interface information that meets functional and scenario requirements; Based on the preset data service specification information, generate the interface modification requirement information for the interface corresponding to the external data service interface information; Based on the fields in the functional requirements information and scenario requirements information, generate import template information for the fields in the knowledge base.
[0007] In one possible implementation, the business requirement information includes business process information; the order in which the data service interface and the entity extraction plugin service interface are called, according to the business requirement information, includes: Based on the business process information, generate the calling order of the data service interface and the entity extraction plugin service interface.
[0008] In one possible implementation, the business requirement information includes the mapping relationship between output data format and chart type; according to the calling order, the program information corresponding to the service interface design information and the knowledge base import information are combined to obtain the first question-and-answer system, including: The program information obtains the mapping relationship between the output data format and the chart type, and the output data format is the data format of the output parameters; According to the order of invocation, the program information corresponding to the service interface design information and the knowledge base import information are combined to obtain the second question system; By combining the second question system and the program information on the mapping relationship between the output data format and the chart type, the first question system is obtained.
[0009] In one possible implementation, the business requirement information includes access component information for the access component, and a mapping relationship between the access component information and the user identifier; after combining the program information corresponding to the service interface design information and the knowledge base import information according to the calling order to obtain the first question-and-answer system, the method further includes: The program information of the access component is combined with the first question system to obtain the third question system; The mapping relationship between access component information and user identifier is input into the third question system so that when the third question system receives a user question, it controls the access permissions of the access component according to the mapping relationship between access component information and user identifier.
[0010] In one possible implementation, after combining the program information corresponding to the service interface design information and the knowledge base import information according to the calling order to obtain the first question-and-answer system, the method further includes: The first question system was tested, and the test results were obtained.
[0011] Secondly, embodiments of this application provide an apparatus for constructing a question-and-answer system, comprising: The acquisition module is used to acquire business requirement information and corresponding data requirement information. The data requirement information includes service interface modification requirement information and import template information for fields in the knowledge base. The generation module is used to generate service interface design information and knowledge base import information according to data requirements. The service interface design information includes the design information of the input parameters of the data service interface, the output parameters of the data service interface, entity extraction prompts, and the output parameters of the entity extraction plugin service interface. The generation module is also used to generate the calling order of the data service interface and the entity extraction plugin service interface according to the business requirements information; The combination module is used to combine the program information corresponding to the service interface design information and the knowledge base import information according to the calling order to obtain the first question system.
[0012] Thirdly, embodiments of this application provide an electronic device, the device comprising: Processor and memory storing computer program instructions; A method for constructing a question-and-answer system that implements any of the above when the processor executes computer program instructions.
[0013] Fourthly, embodiments of this application provide a computer storage medium on which computer program instructions are stored, and when the computer program instructions are executed by a processor, a method for constructing a question-and-answer system that implements any of the above-mentioned methods.
[0014] Fifthly, embodiments of this application provide a computer program product in which instructions, when executed by a processor of an electronic device, enable the electronic device to execute any of the above-mentioned methods for constructing a query system.
[0015] The method, apparatus, device, computer-readable storage medium, and computer program product for constructing a data collection system according to embodiments of this application acquire business requirement information and corresponding data requirement information. The data requirement information includes service interface modification requirement information and import template information for fields in the knowledge base. Based on the data requirement information, service interface design information and knowledge base import information are generated. The service interface design information includes design information for the input parameters, output parameters, entity extraction prompts, and output parameters of the entity extraction plugin service interface. Based on the business requirement information, the calling order of the data service interface and the entity extraction plugin service interface is generated. According to the calling order, the program information corresponding to the service interface design information and the knowledge base import information are combined to obtain a first data collection system. Embodiments of this application cover the entire data collection system construction process, avoiding fragmented implementation. Assembling based on design information ensures implementation consistency and predictability, avoids on-the-fly modifications, and thus shortens the implementation cycle of the data collection system and improves efficiency. Attached Figure Description
[0016] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0017] Figure 1 This is a flowchart illustrating a method for constructing a question-and-answer system according to an embodiment of this application; Figure 2 This is a flowchart illustrating a method for constructing a question-and-answer system according to another embodiment of this application; Figure 3 This is a flowchart illustrating a method for constructing a question-and-answer system according to another embodiment of this application; Figure 4 This is a flowchart illustrating a method for constructing a question-and-answer system according to another embodiment of this application; Figure 5 This is a schematic diagram of the structure of a question-and-answer system construction apparatus provided in another embodiment of this application; Figure 6 This is a schematic diagram of the structure of an electronic device provided in another embodiment of this application. Detailed Implementation
[0018] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.
[0019] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.
[0020] It should be noted that the acquisition, storage, use, and processing of data in this application embodiment all comply with the relevant provisions of national laws and regulations.
[0021] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.
[0022] In the current wave of enterprise digital transformation, conversational business intelligence tools are gradually becoming a key technology for improving decision-making efficiency because they allow users to conveniently query and analyze data using natural language. The realization of its core function, "intelligent data querying," relies on the effective scheduling of heterogeneous backend data services and a precise understanding of domain knowledge.
[0023] However, existing implementation processes for conversational Business Intelligence (BI) tools have significant shortcomings. Current industry practices and related technical solutions primarily focus on specific technical implementations during the system development phase, such as training natural language processing models, parsing and translating query statements, and front-end and back-end interaction design. This limitation leads to numerous challenges for enterprises when introducing and implementing such tools. For example, the implementation of intelligent query systems often falls into a "make-as-you-go" dilemma, resulting in unreasonably prolonged implementation cycles and low efficiency.
[0024] To address the problems of existing technologies, embodiments of this application provide a method, apparatus, device, computer-readable storage medium, and computer program product for constructing a data collection system. The data collection system construction method provided in this application covers the entire data flow of the data collection system construction process, avoiding fragmented implementation. Furthermore, it is assembled based on design information, ensuring implementation consistency and predictability, avoiding on-the-fly modifications, thereby shortening the implementation cycle of the data collection system and improving efficiency.
[0025] To more clearly illustrate the methods provided in the embodiments of this application, the terms involved in the embodiments of this application will be explained below.
[0026] Intelligent Data Search: Based on the instruction extraction capabilities of large models and enhanced retrieval technology, it quickly helps users search for and recommend the data they want to see in natural language. Through the understanding of large models, it describes data trends and correlation data in natural language, reducing the time users spend understanding data charts.
[0027] Intelligent Data Analysis Assistant: Provides assistance with data analysis and application, supports semi-structured queries based on advanced search commands, and supports data analysis of datasets through natural language descriptions, acting as a "navigator for data analysts".
[0028] Implementation process: A set of technical specifications used to guide and standardize the engineering construction, project implementation, and application development of intelligent data.
[0029] Intelligent agent: An entity that can autonomously analyze information and take proactive actions to achieve its goals. Intelligent agents can be software programs (such as intelligent data analysis assistants).
[0030] Knowledge Base: Supports users to upload, update, and maintain knowledge materials according to knowledge space and permission management requirements. After being processed by a word embedding model, the knowledge materials are converted into vector form, becoming vectorized knowledge that can be understood and retrieved by the large model.
[0031] Conversational BI tools, also known as intelligent data analysis platforms that combine large language models and natural language processing, allow users to directly submit data queries and analysis requests through natural language interaction.
[0032] The implementation process includes natural language interaction, data processing and integration, data visualization, and automatic conclusion generation to assist decision-making.
[0033] Among its features are: Natural Language Interaction: Users ask questions in natural language, and the system uses a large language model to understand these questions and translate them into data queries. This interaction method allows non-technical users to easily communicate with the system and obtain the data they need. Data Processing and Integration: The system interacts with multiple data sources to extract and process data. It can convert natural language queries into API calls or SQL queries, thereby automatically retrieving information from different data storage sources. Data Visualization: The system not only provides backend data processing but also visually presents data results to users through charts and graphs. Automatic Conclusion Generation to Assist Decision Making: Based on data analysis results, the system automatically extracts analytical indicators and models analytical models to generate complete analytical conclusions to assist decision making.
[0034] The following is a detailed description of the construction method of the question-and-answer system provided in the embodiments of this application.
[0035] like Figure 1 As shown, the method for constructing a question-and-answer system provided in this application includes the following steps S110 to S140.
[0036] S110. Obtain business requirement information and corresponding data requirement information. The data requirement information includes service interface modification requirement information and import template information for fields in the knowledge base.
[0037] In some embodiments, the business requirement information refers to the business requirement information for the query data system to process business, where the query data system refers to a system that provides intelligent query data functionality. The business requirement information can differ in different application scenarios. When the constructed query data system needs to serve multiple application scenarios simultaneously, it is necessary to obtain business requirement information from multiple application scenarios.
[0038] In some embodiments, business requirement information includes business requirement fields. The business requirement fields in the received business requirement information are extracted to conduct in-depth analysis of the specific functions that the intelligent agent of the data query system needs to implement and the actual scenarios in which these functions will be applied. Data requirement information corresponding to the functions and scenarios is then obtained.
[0039] In one example, the system receives business requirement information input by the user.
[0040] In another example, the system receives business requirement information sent by a target device, which represents the device of the requester in the data system.
[0041] In some embodiments, the data sources for the functions and scenarios of the data query system are obtained. Based on the data sources, the data service interfaces used by the functions and scenarios of the data query system are determined. These data service interfaces include internal data service interfaces and external data service interfaces. According to preset data specification information, service interface modification requirement information for the data service interfaces is generated.
[0042] Among them, the preset data specification information is the data specification information for large models.
[0043] In one example, the data query system is built within an existing data service platform. The data source for obtaining data that meets the functions and scenarios of the data query system is the existing data service platform, which provides internal data service interfaces.
[0044] In another example, the user's first input is received, which includes interface information from an external data service interface.
[0045] In some embodiments, initial fields from the knowledge base are obtained. If the initial fields in the knowledge base do not meet the input parameters of the data service interface, import template information for the fields in the knowledge base is generated. This import template information restricts the mapping relationship between fields and field numbers, representing the import standard information for the fields in the knowledge base. For example, fields may include indicators and organizations.
[0046] S120. Based on the data requirements information, generate service interface design information and knowledge base import information. The service interface design information includes the design information of the input parameters of the data service interface, the output parameters of the data service interface, entity extraction prompts, and the output parameters of the entity extraction plugin service interface.
[0047] It should be noted that the input parameter for the entity extraction plugin service interface is the entity extraction prompt word.
[0048] In some embodiments, design information for the input parameters and output parameters of the data service interface is generated according to the service interface modification information of the data service interface. The input parameters include input field names and input field types (or input field formats), and the output parameters include output field names and output field types (or output field formats). The input parameters of the data service interface generated according to the service interface modification information are the parameters output by the large model after processing; the output parameters of the data service interface generated according to the service interface modification information are the parameters that can be input into the large model. The data service interface includes internal data service interfaces and external data service interfaces.
[0049] Understandably, large models can process data based on the output parameters of data service interfaces to generate the results required by users.
[0050] In some embodiments, to enable the invocation of a data service interface using entity keywords from a user question, design information is provided for generating input and output parameters for an entity extraction plugin service interface. It is understood that the input parameter for the entity extraction plugin service interface is entity extraction hints, which the large model uses to extract entity keywords from the user question. Furthermore, the extracted entity keywords are used as input parameters for the entity extraction plugin service interface. After processing the entity keywords using the entity extraction plugin, the output parameters of the entity extraction plugin service interface are obtained. The output parameters of the entity extraction plugin service interface satisfy the invocation of the data service interface and the program processing logic for the input parameters of the data service interface.
[0051] In one example, the entity keyword is the organization name.
[0052] In some embodiments, the entity extraction plugin internally calls a knowledge base for matching, rearrangement, and logical processing, ultimately outputting fully standardized output parameters that can directly drive downstream data service interfaces, thereby improving the accuracy of entity extraction.
[0053] In this embodiment, design information for the internal processing logic of the entity extraction plugin can also be generated.
[0054] In some embodiments, data retrieval permissions, request headers, request bodies, and return results for the data service interface can also be generated according to data requirement information.
[0055] In some embodiments, initial import information for the knowledge base is obtained. This initial import information is then processed according to the import template information to obtain the knowledge base import information. This knowledge base import information must meet the matching requirements of the entire question-and-answer system.
[0056] In one example, the system receives initial import information for the knowledge base from user input.
[0057] In another example, the initial import information for the knowledge base sent by the target device is received.
[0058] S130. Based on the business requirements information, generate the calling order of the data service interface and the entity extraction plugin service interface.
[0059] In some embodiments, the agent type is recorded. Agent types include newly created agents and reused agents. When the agent type is a newly created agent, the calling order of the data service interface and the entity extraction plugin service interface is generated according to the business requirement information, and workflow orchestration information corresponding to the calling order of the data service interface and the entity extraction plugin service interface is generated.
[0060] In some embodiments, external data service interfaces are marked to distinguish them from internal data service interfaces.
[0061] In some embodiments, the business requirements information may differ under different functions and application scenarios, so the order of calling the data generation service interface and the entity extraction plugin service interface will also be different.
[0062] S140. According to the calling order, combine the program information and knowledge base import information corresponding to the service interface design information to obtain the first question system.
[0063] In some embodiments, the program information corresponding to the service interface design information is obtained, and the program information corresponding to the service interface design information and the knowledge base import information are combined according to the calling order to obtain the first question system.
[0064] In one example, the program information corresponding to the service interface design information is automatically generated.
[0065] In another example, the program information corresponds to the service interface design information received from the user.
[0066] It should be noted that the program information corresponding to the service interface design information needs to be developed based on the service interface design information. At the same time, network access relationships and security node policies need to be enabled, and the application programming interface (API) needs to be published for downstream calls.
[0067] In some embodiments, the imported knowledge base information is converted into vector form and then written to the knowledge base vector library. After all the imported knowledge base information is written to the knowledge base vector library, an upload success message is generated.
[0068] In some embodiments, before combining the program information corresponding to the service interface design information and the knowledge base import information according to the calling order to obtain the first question-and-answer system, it is necessary to prepare the environment and build the necessary operating environment, such as server resources and network configuration. Then, the large model is connected and adapted, its parameters are adjusted, and the large model is integrated into the intelligent question-and-answer workflow.
[0069] Understandably, it is necessary to follow the API documentation provided by the large model, correctly construct the request parameters, and call the corresponding service interfaces.
[0070] In some embodiments, the first questioning system configures relevant business parameters for the intelligent agent, including prompt words, intelligent agent name, large model parameters, and greetings, to facilitate user use.
[0071] The embodiments of this application cover the entire process of data construction for the data collection system, avoiding fragmented implementation and assembling based on design information to ensure consistency and predictability in implementation, avoiding on-the-fly modifications, thereby shortening the implementation cycle of the data collection system and improving efficiency.
[0072] In some embodiments, business requirement information includes functional requirement information and scenario requirement information; such as Figure 2 As shown, in the above S110, obtaining the data requirement information corresponding to the business requirement information may include S111 to S115.
[0073] S111. Obtain the initial output parameters of the initial question system using the internal data service interface of the initial question system.
[0074] In some embodiments, the initial data query system is built on an existing data service platform. The initial output parameters of the initial data query system are obtained using its internal data service interface. These initial output parameters are parameters already configured on the data service platform.
[0075] S112. If the initial output parameters cannot meet the functional requirements and scenario requirements, generate service interface modification requirements for the internal data service interface.
[0076] In some embodiments, it is detected whether the initial output parameters can meet the functional requirements and scenario requirements. If the initial output parameters cannot meet the functional requirements and scenario requirements, service interface modification requirements for the internal data service interface are generated.
[0077] In some embodiments, it is detected whether the data retrieval logic of the initial output parameters can meet the functional requirements and scenario requirements. If the data retrieval logic of the initial output parameters cannot meet the functional requirements and scenario requirements, service interface modification requirements for the internal data service interface are generated.
[0078] S113. Obtain external data service interface information that meets functional and scenario requirements.
[0079] In some embodiments, to satisfy functional and scenario requirements, it is necessary to call an external data service interface. This involves obtaining information about the external data service interface that satisfies the functional and scenario requirements.
[0080] In one example, the external data service interface receives user input.
[0081] S114. Generate interface modification requirements for the interfaces corresponding to the external data service interface information according to the preset data service specification information.
[0082] Among them, the preset data service specification information is the data service specification information oriented towards large models.
[0083] In some embodiments, the input and output parameters of the external data service interface may not meet the data service specification information of the large model. Therefore, it is necessary to generate interface modification requirements for the interface corresponding to the external data service interface information based on the data service specification information for the large model, so as to adapt to the large model.
[0084] S115. Based on the fields in the functional requirements information and scenario requirements information, generate import template information for the fields in the knowledge base.
[0085] In some embodiments, initial fields from the knowledge base are obtained. If the initial fields in the knowledge base cannot satisfy the input parameters of the data service interface, import template information for the fields in the knowledge base is generated based on the fields in the functional requirements information and scenario requirements information. The import template information restricts the mapping relationship between fields and field numbers, representing the standard information for importing fields from the knowledge base. For example, fields include indicators and organizations.
[0086] This application embodiment determines the modification requirements of the data service interface and the import template information of the fields in the knowledge base by using the functional requirements and scenario requirements of the question-and-answer system. This makes the question-and-answer system built according to the modification requirements and the import template information of the fields in the knowledge base more in line with business needs, reduces rework problems caused by failure to meet business needs, and improves implementation efficiency.
[0087] In some embodiments, business requirement information includes business process information; S130 above may specifically include: Based on the business process information, generate the calling order of the data service interface and the entity extraction plugin service interface.
[0088] Among them, business process information refers to the business process information of the question data system from receiving instructions to completing tasks.
[0089] The embodiments of this application generate the calling order of the data service interface and the entity extraction plugin service interface according to the actual business process information, which is more in line with business requirements, reduces rework problems caused by failure to meet business requirements, and improves implementation efficiency.
[0090] In some embodiments, business requirement information includes a mapping relationship between output data formats and chart types; such as Figure 3 As shown, S140 can specifically include S141 to S143.
[0091] S141. Obtain program information on the mapping relationship between output data format and chart type. The output data format is the data format of the output parameters.
[0092] In some embodiments, to make the results output by the data query system more user-friendly and improve user experience, the results need to be displayed in chart form. Program information that maps output data formats to chart types is obtained to enable the data query system to display charts. The output data format refers to the data format of the output parameters. For example, the output parameters are those obtained after calling the last data service interface.
[0093] In one example, the program receives user input and maps the output data format to the chart type.
[0094] In another example, the program receives the mapping relationship between the output data format and the chart type from user input, and automatically generates the program information of the mapping relationship between the output data format and the chart type based on the mapping relationship.
[0095] S142. According to the calling order, combine the program information and knowledge base import information corresponding to the service interface design information to obtain the second question system.
[0096] In some embodiments, the program information and knowledge base import information corresponding to the service interface design information are first combined according to the calling order to obtain the second question system, and then the chart display function is inserted into the second question system.
[0097] S143. Combine the second question system and the program information on the mapping relationship between the output data format and the chart type to obtain the first question system.
[0098] In some embodiments, the second questioning system and the program information mapping the output data format to the chart type are combined so that the resulting first questioning system displays the output results in chart form.
[0099] The chart types can include, but are not limited to, line charts and bar charts.
[0100] This application embodiment combines program information on the mapping relationship between output data format and chart type into the question-and-answer system, thereby increasing the chart display function of the question-and-answer system, making it more convenient for users to use and improving the user experience.
[0101] In some embodiments, the business requirement information includes access component information of the access component, and the mapping relationship between the access component information and the user identifier; such as Figure 4 As shown, after S140 above, the method may also include S150 to S160.
[0102] S150. Combine the program information of the access component with the first question system to obtain the third question system.
[0103] In some embodiments, the first query system can integrate multiple access components to provide different functions. The program information of the access components is obtained, and this information is combined with the first query system to obtain a third query system.
[0104] It should be noted that the access components include front-end display components and back-end logic processing components.
[0105] S160. Input the mapping relationship between access component information and user identifier into the third question system, so that when the third question system receives a user question, it controls the access permissions of the access component according to the mapping relationship between access component information and user identifier.
[0106] The access to component information includes component number, component name, component path, component Uniform Resource Locator (URL) path, component permissions, and component permission number. Clear navigation provided by the component can improve the user experience.
[0107] In some embodiments, access components can be customized, with different access components available to users in different roles. The mapping relationship between access component information and user identifiers in the business requirement information is input into the third-party query system, so that when the third-party query system receives a user question, it controls access permissions to the access components according to the mapping relationship between the access component information and the user identifier.
[0108] It should be noted that, in this embodiment of the application, the mapping relationship between the data service interface and the user identifier can also be input into the third question system, so that when the third question system receives a user question, the calling permission of the data service interface can be controlled according to the mapping relationship between the data service interface and the user identifier.
[0109] This application embodiment adds functionality to the question-and-answer system by accessing component settings, thereby enhancing the user experience.
[0110] In some embodiments, after combining the program information corresponding to the service interface design information and the knowledge base import information according to the invocation order to obtain the first question-and-answer system, the method further includes: The first question system was tested, and the test results were obtained.
[0111] In some embodiments, the testing includes functional testing. Functional test cases are obtained based on the functions and application scenarios of the intelligent data analysis system. The first data analysis system is then functionally tested using the intelligent data analysis assistant platform by inputting the functional test cases and test data, and the test results are obtained.
[0112] In some embodiments, testing includes user testing. Based on the functions and application scenarios of the intelligent data collection system, user test cases are obtained. Through an intelligent data analysis assistant platform, the user test cases and test data are input to perform functional testing on the first data collection system, and the test results are obtained. It should be noted that the data collection system can be iteratively optimized using user test cases and test data.
[0113] In some embodiments, the testing includes non-functional testing. Based on the functions and application scenarios of the intelligent query system, non-functional test cases are obtained. Using a non-functional testing tool, these test cases are input, and non-functional test scripts are executed to perform functional testing on the data service interface and entity extraction plugin service interface of the first query system, thereby obtaining the test results.
[0114] In one example, non-functionality refers to the predetermined quality standards that the system meets, such as response time, number of concurrent users, and data integrity.
[0115] The embodiments of this application can verify the effectiveness of the first questioning system by testing it, so as to find the system problems through design information, program information, etc. when appropriate, thereby improving implementation efficiency.
[0116] Many companies face a series of challenges when trying to introduce conversational BI tools, including but not limited to long implementation cycles, serious waste of resources, frequent quality problems, and difficulty in responding to changes in future business needs. Traditional tools may not be able to adapt well to the specific needs and special scenarios of different companies, resulting in inconsistent implementation results, unreasonable resource allocation, high hardware costs, and extended project cycles.
[0117] This application embodiment constructs a systematic and standardized engineering implementation framework for intelligent data querying, covering all aspects from business requirements, design information, program information, and testing, ensuring standardization and normalization during the implementation of the intelligent data querying system. It also provides clear operational steps, effectively improving the quality and efficiency of intelligent data querying system implementation, avoiding repetitive work, accelerating the process, and enabling early detection and resolution of problems, effectively preventing potential risks, reducing the possibility of rework later, and solving the problems of the aforementioned prior art.
[0118] Furthermore, this application's embodiments enable implementers to quickly grasp the core essentials from all aspects, including business requirements, design information, program information, and testing, providing a reliable basis for subsequent review and continuous optimization. This application's embodiments have achieved significant breakthroughs in standardization, normalization, and refinement, providing a more efficient, reliable, and easy-to-operate implementation path for the engineering of intelligent data collection, enabling the implementation of intelligent data collection systems at lower costs and higher efficiency, effectively avoiding unnecessary hardware investment and wasted manpower.
[0119] Based on the method for constructing a question-and-answer system provided in the above embodiments, this application also provides specific implementations of a device for constructing a question-and-answer system. Please refer to the following embodiments.
[0120] See Figure 5 The question-and-answer system construction apparatus 300 provided in this application embodiment includes: The acquisition module 310 is used to acquire business requirement information and corresponding data requirement information. The data requirement information includes service interface modification requirement information and import template information of fields in the knowledge base. The generation module 320 is used to generate service interface design information and knowledge base import information according to data requirement information. The service interface design information includes the design information of the input parameters of the data service interface, the output parameters of the data service interface, entity extraction prompts, and the output parameters of the entity extraction plugin service interface. The generation module 320 is also used to generate the calling order of the data service interface and the entity extraction plugin service interface according to the business requirement information; The combination module 330 is used to combine the program information corresponding to the service interface design information and the knowledge base import information according to the calling order to obtain the first question system.
[0121] In some embodiments, business requirement information includes functional requirement information and scenario requirement information; the acquisition module 310 can specifically be used for: Use the internal data service interface of the initial question system to obtain the initial output parameters of the initial question system; If the initial output parameters cannot meet the functional and scenario requirements, generate service interface modification requirements for the internal data service interface. Obtain external data service interface information that meets functional and scenario requirements; Based on the preset data service specification information, generate the interface modification requirement information for the interface corresponding to the external data service interface information; Based on the fields in the functional requirements information and scenario requirements information, generate import template information for the fields in the knowledge base.
[0122] In some embodiments, business requirement information includes business process information; the generation module 320 can specifically be used for: Based on the business process information, generate the calling order of the data service interface and the entity extraction plugin service interface.
[0123] In some embodiments, business requirement information includes a mapping relationship between output data format and chart type; the combination module 330 can specifically be used for: The program information obtains the mapping relationship between the output data format and the chart type, and the output data format is the data format of the output parameters; According to the order of invocation, the program information corresponding to the service interface design information and the knowledge base import information are combined to obtain the second question system; By combining the second question system and the program information on the mapping relationship between the output data format and the chart type, the first question system is obtained.
[0124] In some embodiments, the business requirement information includes access component information of the access component, and a mapping relationship between the access component information and the user identifier; the device 300 may further include: The combination module is used to combine the program information corresponding to the service interface design information and the knowledge base import information according to the calling order to obtain the first question system, and then combine the program information of the access component with the first question system to obtain the third question system. The input module is used to input the mapping relationship between access component information and user identifier into the third question system, so that when the third question system receives a user question, it can control the access permissions of the access component according to the mapping relationship between the access component information and the user identifier.
[0125] In some embodiments, the device 300 may further include: The testing module is used to combine the program information and knowledge base import information corresponding to the service interface design information according to the calling order to obtain the first question system, and then test the first question system to obtain the test results.
[0126] Each module of the question-and-answer system construction apparatus provided in this application embodiment can realize the functions of each step of the question-and-answer system construction method provided above, and can achieve its corresponding technical effects. For the sake of brevity, it will not be described in detail here.
[0127] Based on the same inventive concept, embodiments of this application also provide an electronic device.
[0128] Figure 6 A schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application is shown.
[0129] An electronic device may include a processor 401 and a memory 402 storing computer program instructions.
[0130] Specifically, the processor 401 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.
[0131] Memory 402 may include mass storage for data or instructions. For example, and not limitingly, memory 402 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 402 may include removable or non-removable (or fixed) media. Where appropriate, memory 402 may be internal or external to an electronic device. In a particular embodiment, memory 402 is a non-volatile solid-state memory.
[0132] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the methods according to one aspect of this disclosure.
[0133] The processor 401 reads and executes computer program instructions stored in the memory 402 to implement any of the question-and-answer system construction methods in the above embodiments.
[0134] In one example, the electronic device may also include a communication interface 403 and a bus 410. For example, Figure 6 As shown, the processor 401, memory 402, and communication interface 403 are connected through bus 410 and complete communication with each other.
[0135] The communication interface 403 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.
[0136] Bus 410 includes hardware, software, or both, that couples components of an electronic device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Linear Predictive Coding (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (Peripheral Component Interconnect-X, PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VESA Local Bus, VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 410 may include one or more buses. Although specific buses are described and illustrated in the embodiments of this application, this application contemplates any suitable bus or interconnection. The electronic device can execute the question-and-answer system construction method of the embodiments of the present invention, thereby implementing the question-and-answer system construction method described above.
[0137] Furthermore, in conjunction with the method for constructing the question-and-answer system in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the question-and-answer system construction methods in the above embodiments.
[0138] This application also provides a computer program product, wherein the instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform various processes implementing any of the above-described embodiments of the question-and-answer system construction method.
[0139] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.
[0140] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memory (ROM), flash memory, erasable read-only memory (EROM), floppy disks, compact disc read-only memory (CD-ROM), optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.
[0141] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.
[0142] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.
[0143] The above are merely specific embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.
Claims
1. A method of constructing a question system, characterized by, The method comprises the following steps: obtaining business requirement information and data requirement information corresponding to the business requirement information, wherein the data requirement information comprises service interface reconstruction requirement information and import template information of fields in a knowledge base; generating service interface design information and knowledge base import information according to the data requirement information, wherein the service interface design information comprises design information of input parameters of a data service interface, output parameters of the data service interface, entity extraction prompt words and output parameters of an entity extraction plug-in service interface; generating a calling sequence of the data service interface and the entity extraction plug-in service interface according to the business requirement information; combining program information corresponding to the service interface design information and the knowledge base import information according to the calling sequence to obtain a first question system.
2. The method of claim 1, wherein, The business requirement information comprises function requirement information and scene requirement information; obtaining data requirement information corresponding to the business requirement information comprises the following steps: obtaining initial output parameters of an initial question system by using an internal data service interface of the initial question system; generating service interface reconstruction requirement information of the internal data service interface in a case where the initial output parameters cannot meet the function requirement information and the scene requirement information; obtaining external data service interface information meeting the function requirement information and the scene requirement information; generating interface reconstruction requirement information of an interface corresponding to the external data service interface information according to preset data service specification information; generating import template information of fields in a knowledge base according to fields in the function requirement information and the scene requirement information.
3. The method of claim 1, wherein, The business requirement information comprises business process information; the generating of the calling sequence of the data service interface and the entity extraction plug-in service interface according to the business requirement information comprises the following step: generating the calling sequence of the data service interface and the entity extraction plug-in service interface according to the business process information.
4. The method of claim 1, wherein, The business requirement information comprises a mapping relationship between an output data format and a chart type; the combining of the program information corresponding to the service interface design information and the knowledge base import information according to the calling sequence to obtain the first question system comprises the following steps: obtaining program information of the mapping relationship between the output data format and the chart type, wherein the output data format is a data format of output parameters; combining the program information corresponding to the service interface design information and the knowledge base import information according to the calling sequence to obtain a second question system; combining the second question system and the program information of the mapping relationship between the output data format and the chart type to obtain the first question system.
5. The method according to any one of claims 1 to 4, characterized in that, The business requirement information comprises access component information of an access component and a mapping relationship between the access component information and a user identifier; after the combining of the program information corresponding to the service interface design information and the knowledge base import information according to the calling sequence to obtain the first question system, the method further comprises the following steps: combining program information of the access component and the first question system to obtain a third question system. The mapping relationship between the access component information and the user identification is input to the third question system, so that the access right of the access component is controlled according to the mapping relationship between the access component information and the user identification when the user question is received by the third question system.
6. The method of claim 1, wherein, After the program information corresponding to the service interface design information and the knowledge base import information are combined according to the calling sequence to obtain the first question system, the method further comprises: The first question system is tested to obtain a test result.
7. A construction device of a question system, characterized by comprising: Comprise: An acquisition module is configured to acquire business requirement information and data requirement information corresponding to the business requirement information, the data requirement information comprising service interface reconstruction requirement information and import template information of fields in a knowledge base; A generation module is configured to generate service interface design information and knowledge base import information according to the data requirement information, the service interface design information comprising design information of input parameters of a data service interface, output parameters of the data service interface, entity extraction prompt words and output parameters of an entity extraction plug-in service interface; The generation module is further configured to generate a calling sequence of the data service interface and the entity extraction plug-in service interface according to the business requirement information; A combination module is configured to combine program information corresponding to the service interface design information and the knowledge base import information according to the calling sequence to obtain a first question system.
8. An electronic device, comprising: The device comprises a processor and a memory storing computer program instructions; The processor executes the computer program instructions to implement the construction method of the question system according to any one of claims 1-6.
9. A computer-readable storage medium, characterized in that, The computer program instructions are stored on the computer readable storage medium, and the computer program instructions are executed by the processor to implement the construction method of the question system according to any one of claims 1-6.
10. A computer program product, characterised in that, The instructions in the computer program product are executed by the processor of the electronic device, so that the electronic device can execute the construction method of the question system according to any one of claims 1-6.