Digital service scheme generation method and system based on product demand library, and medium

Abstract

The present application relates to the technical field of large-scale engineering digital service and data processing, and specifically provides a digital service scheme generation method and system based on a product demand library and a medium, the method comprising: obtaining a user terminal original demand text and performing semantic analysis, extracting demand semantic features, matching a candidate function element set from the product demand library, screening and sorting according to the matching confidence, and combining user feedback to check and generate a function element list; retrieving display, data and basic hardware requirements according to the function element list, using a random forest regression model, a multi-objective optimization function and a knowledge graph embedding to complete hardware optimization and adaptation, and aggregating various requirements to generate a differentiated requirement configuration scheme; integrating the requirement configuration scheme, combining price prediction and budget pricing to generate a service scheme configuration data package, filling a standardized report template, and outputting a structured requirement report. The present application realizes requirement matching and hardware configuration optimization, improves the efficiency of digital scheme compilation, and reduces project design and communication costs.

Description

Technical Field

[0001] This invention relates to the field of digital services and data processing technology for large-scale engineering projects, specifically to a method, system, and medium for generating digital service solutions based on a product requirement database. Background Technology

[0002] In the field of digital services for large-scale engineering projects (such as offshore wind power, hydropower, and municipal engineering), existing technologies typically employ an implementation model based on customized development. Under this model, after a user submits a business request, the service provider must sequentially complete tasks such as requirements analysis, solution design, software function configuration, data service matching, and hardware equipment selection and pricing. However, the following problems commonly exist in the above-mentioned technological implementation process: First, there is a lack of standardization in the expression of requirements. User requirements are often presented as unstructured, incomplete, or semantically ambiguous text information. The lack of unified expression standards leads to reliance on human interpretation in the requirement parsing process, which is prone to bias and increases communication costs.

[0003] Secondly, the efficiency of solution generation is low. In existing technologies, the formation of service solutions mainly relies on human experience to match and combine functional modules, data resources, and hardware devices. The degree of automation is low, which not only limits efficiency but also makes it difficult to guarantee the completeness and accuracy of the solution.

[0004] Secondly, there is insufficient correlation between requirements. In existing solutions, there is usually a lack of a unified correlation mechanism between functional requirements, data support requirements, visualization requirements, and hardware configuration requirements. This results in various requirements being fragmented, making it difficult to automatically generate a complete list of data requirements and hardware configurations corresponding to the functional requirements after the solution is generated. This can easily lead to omissions or inconsistencies in configuration during subsequent implementation.

[0005] Furthermore, existing technologies struggle to achieve structured reuse of knowledge. Functional modules, solutions, and related experiences from past projects typically exist in the form of documents or scattered data, lacking a unified structured management approach. This makes it difficult to reuse related knowledge, thus requiring repeated requirements analysis and solution design in new projects.

[0006] Therefore, there is an urgent need to develop a new method and system for generating digital service solutions based on a product requirement database, so as to realize the structured expression of requirements, the standardized organization of service capabilities, and the automatic generation of solutions, thereby improving the efficiency and accuracy of digital service solution configuration and enhancing the reusability of relevant knowledge. Summary of the Invention

[0007] This invention addresses the problems of high customization, slow solution generation, fragmented functional data and hardware, and difficulty in knowledge reuse in traditional large-scale engineering digital services. It provides a method, system, and medium for generating digital service solutions based on a product requirement database, thereby achieving requirement standardization, solution automation, and knowledge assetization.

[0008] To achieve the above objectives, the present invention adopts one or more of the following technical solutions: In a first aspect, the present invention provides a method for generating digital service solutions based on a product demand database, comprising the following steps: The system obtains the original requirement text sent by the user, performs semantic parsing on the original requirement text to obtain requirement semantic features, matches a set of candidate functional elements from a pre-set product requirement database based on the requirement semantic features, outputs the matching confidence of each candidate functional element, filters and sorts the candidate functional elements in the candidate functional element set based on the matching confidence, generates a recommended functional element set, obtains feedback data from the user on the recommended functional element set, verifies the recommended functional element set based on the feedback data, and generates a functional element list. Based on the functional element list, a related search is performed in the pre-set related requirement library to obtain the corresponding display requirements, data requirements and basic hardware requirements. The basic hardware requirements are optimized and adapted using a random forest regression model, a multi-objective optimization function and knowledge graph embedding to obtain the final hardware requirements. The display requirements, data requirements and hardware requirements are aggregated to generate multiple sets of differentiated requirement configuration schemes. The aforementioned demand configuration schemes are structured and integrated, and a digital service solution configuration data package is generated by predicting price fluctuations and adjusting pricing according to budget. The configuration data package of the digital service solution is populated into a preset standardized report template to generate a structured requirements report.

[0009] Furthermore, the method also includes: The structured requirements report is productized and packaged into a digital product with standardized pricing and delivery models, and the digital product is stored in the product catalog.

[0010] Furthermore, the method also includes: Building a product requirements library specifically includes: The server acquires digital service capability data and, according to a pre-set data hierarchy structure, splits the digital service capability data. The pre-set data hierarchy structure includes at least a strategy layer, a business layer, a functional layer, and functional elements that are broken down layer by layer. Each functional element is associated with a unique three-dimensional label, which includes a display requirement label, a data requirement label, and a hardware requirement label. Building a related requirements library, specifically including: Obtain the display resource data, data resource data, and hardware resource data corresponding to each functional element, and construct a display requirement library, a data requirement library, and a hardware requirement library respectively. The display requirement library, the data requirement library, and the hardware requirement library are associated with the functional element through ID identification.

[0011] Furthermore, feedback data from users regarding the recommended feature set is obtained, and the recommended feature set is verified based on the feedback data to generate a feature list, specifically including: A pre-trained language model is used to perform syntactic analysis and intent recognition on the original requirement text, and a hierarchical requirement semantic vector is constructed to obtain requirement semantic features. Based on graph convolutional neural networks, the association relationship between functional elements in the product requirement database is learned, and a semantic similarity matrix between functional elements is generated. Based on the semantic features of the requirements, a set of candidate functional elements is obtained by matching from the product requirement database, and the matching confidence of each candidate functional element is output. The candidate functional element set is filtered and sorted according to the matching confidence to generate a recommended functional element set. Based on the semantic similarity matrix, the functional elements in the recommended functional element set are combined and recommended. When the matching confidence level is lower than a preset threshold, a multi-round interaction process is initiated, and the matching result is iteratively updated based on the response data fed back by the user until a matching result with high confidence level is obtained. The recommended feature set is verified based on the high-confidence matching results to generate a feature list.

[0012] Furthermore, the aforementioned display requirements, data requirements, and hardware requirements are aggregated to generate multiple differentiated requirement configuration schemes, specifically including: Based on the functional element list, perform related searches and requirement matching in the related requirement library to obtain the corresponding display requirements, data requirements and basic hardware requirements. Based on the basic hardware requirements, and combined with historical project data, the project scale and environmental factors are extracted as correlation features, and a random forest regression model is constructed to predict the number of various hardware devices. Using the cost, performance, and scalability of hardware devices as optimization objectives, a multi-objective optimization function is constructed. Combined with the predicted number of hardware devices, the hardware configuration corresponding to the basic hardware requirements is dynamically adjusted to generate the initial hardware configuration. The compatibility constraint relationships between hardware devices are mined using knowledge graph embedding. The initial hardware configuration is checked for compatibility constraints, and hardware configurations that do not meet the compatibility constraint requirements are filtered out. Hardware configurations with compatibility conflicts are replaced and adapted to obtain the final hardware requirements. The aforementioned display requirements, data requirements, and hardware requirements are aggregated to generate multiple differentiated requirement configuration schemes.

[0013] Furthermore, the display requirements include at least the requirements for visualization components, interface design specifications, and resolution; and / or The data requirements include at least data interface protocol requirements, data table structure requirements, data acquisition frequency requirements, and data format requirements; and / or The hardware requirements include at least the hardware device model requirements, device specification requirements, device unit price requirements, device quantity requirements, and total device price requirements.

[0014] Furthermore, the aforementioned demand configuration schemes are structurally integrated, and a digital service solution configuration data package is generated through price fluctuation prediction and budget-adaptive pricing, specifically including: A time series forecasting model is used to predict the prices of various hardware devices and their associated cloud services, and to obtain price fluctuation trends. Obtain the user's budget data, combine it with the price fluctuation trend to generate a pricing strategy, and calculate the estimated price range for each demand configuration scheme; The pricing strategy and estimated price range are linked with the demand configuration plan to generate a digital service solution configuration data package.

[0015] Furthermore, the structured requirements report includes a list of functional requirements, detailed supporting data requirements, visualized deliverables, and hardware configuration information, wherein: The functional requirements list shall include at least the functional elements and their corresponding quantity parameters; The detailed requirements for the supporting data include at least the data interface protocol, data table structure, and data collection frequency. The visualized delivery information includes at least the interface design specifications, chart types, and interaction methods. The hardware configuration information includes at least a list of devices, the quantity of devices, the unit price of devices, and the total price of devices.

[0016] Secondly, the present invention provides a digital service solution generation system based on a product demand database, comprising: The requirement library construction module is used to build product requirement libraries and related requirement libraries; The requirement parsing and matching module is used to obtain the original requirement text sent by the user, perform semantic parsing on the original requirement text to obtain requirement semantic features, match the candidate functional elements set from the pre-set product requirement library based on the requirement semantic features, and output the matching confidence of each candidate functional element. Based on the matching confidence, the candidate functional elements in the candidate functional element set are filtered and sorted to generate a recommended functional element set. The module obtains feedback data from the user on the recommended functional element set, verifies the recommended functional element set based on the feedback data, and generates a functional element list. The solution configuration and assembly module is used to perform related searches in a pre-set related requirement library based on the functional element list to obtain the corresponding display requirements, data requirements, and basic hardware requirements. It then uses a random forest regression model, multi-objective optimization functions, and knowledge graph embedding to optimize and adapt the basic hardware requirements, resulting in the final hardware requirements. The module aggregates the display requirements, data requirements, and hardware requirements to generate multiple differentiated requirement configuration schemes. Finally, it integrates these requirement configuration schemes in a structured manner and generates a digital service solution configuration data package through price fluctuation prediction and budget-adaptive pricing. The report generation module is used to populate the digital service solution configuration data package into a preset standardized report template to generate a structured requirements report.

[0017] Thirdly, the present invention provides a non-volatile computer storage medium storing computer-executable instructions configured to implement the above-described method.

[0018] The technical solution of this invention can achieve the following beneficial effects: (1) Realize knowledge structuring and assetization: By constructing a core product demand library with a four-level hierarchical structure and three related demand libraries for display, data and hardware, and by establishing a relationship with unique identifiers and three-dimensional tags, the enterprise's scattered and implicit project experience is transformed into structured digital assets, which facilitates unified management and reuse, and solves the problem of knowledge being difficult to accumulate and reuse.

[0019] (2) Significantly improve the efficiency and quality of solution preparation: Through the automated process of demand analysis, function matching, related search aggregation, and structured organization, the solution configuration can be completed quickly, greatly reducing the reliance on manual labor and shortening the solution preparation cycle; at the same time, the completeness and accuracy of functions, display, data, and hardware information are guaranteed, reducing human error.

[0020] (3) Achieve strong association between functions, data and hardware: Establish a stable association between functional elements and three types of related requirements with a unique identifier. When the solution is generated, the corresponding display, data and hardware information can be automatically brought out simultaneously to ensure that the solution content is consistent and complete, provide accurate basis for project budget, procurement and implementation, and reduce the risk of later changes and omissions.

[0021] (4) Support digital service productization and agile pricing: It can realize menu-style combination configuration based on functional elements, automatically calculate the total price and generate a hardware configuration list by combining hardware information, support real-time pricing and solution productization packaging, facilitate the formation of standardized digital products, and improve the project reuse and market promotion capabilities.

[0022] (5) Improve communication efficiency and interactive experience: By generating standardized and structured requirement reports, the communication language and delivery standards between service providers and owners are unified, information discrepancies are reduced, and communication efficiency and project delivery are improved. Attached Figure Description

[0023] Figure 1 This is a flowchart of the method for generating digital service solutions based on a product demand database in an embodiment of the present invention; Figure 2 This is a schematic diagram of the four-level hierarchy and three-dimensional tags of the core product demand library in this embodiment of the invention; Figure 3 This is a flowchart illustrating the generation of a requirement report in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of the digital service solution generation system based on the product demand database in an embodiment of the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will now be described in detail and completely with reference to the accompanying drawings. It should be noted that the described embodiments are merely some examples of the present invention and do not represent all possible implementations of the present invention. Any other implementations obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the protection scope of the present invention.

[0025] Figure 1 This is a flowchart of a method for generating digital service solutions based on a product demand database in an embodiment of the present invention.

[0026] The method flow steps of the embodiments in this specification are as follows: The system obtains the original requirement text sent by the user, performs semantic parsing on the original requirement text to obtain requirement semantic features, matches a set of candidate functional elements from a pre-set product requirement database based on the requirement semantic features, outputs the matching confidence of each candidate functional element, filters and sorts the candidate functional elements in the candidate functional element set based on the matching confidence, generates a recommended functional element set, obtains feedback data from the user on the recommended functional element set, verifies the recommended functional element set based on the feedback data, and generates a functional element list. Based on the functional element list, a related search is performed in the pre-set related requirement library to obtain the corresponding display requirements, data requirements and basic hardware requirements. The basic hardware requirements are optimized and adapted using a random forest regression model, a multi-objective optimization function and knowledge graph embedding to obtain the final hardware requirements. The display requirements, data requirements and hardware requirements are aggregated to generate multiple sets of differentiated requirement configuration schemes. The aforementioned demand configuration schemes are structured and integrated, and a digital service solution configuration data package is generated by predicting price fluctuations and adjusting pricing according to budget. The configuration data package of the digital service solution is populated into a preset standardized report template to generate a structured requirements report.

[0027] The structured requirements report is productized and packaged into a digital product with standardized pricing and delivery models, and the digital product is stored in the product catalog.

[0028] Specifically, this embodiment uses the construction of an offshore wind power project visualization platform as an application scenario.

[0029] Methods for constructing a product requirement database include: The digital service capability data provided by enterprises is broken down and structured according to a pre-defined four-level hierarchical structure to construct a core product requirement library. This four-level hierarchical structure includes a strategic layer, business domains, functional groups, and functional elements. The strategic layer defines business strategic objectives, business domains divide core business areas, functional groups aggregate specific functional modules, and functional elements are the smallest deliverable functional units. Each functional element is assigned a unique identifier and a three-dimensional label is set for each element, including display requirement labels, data requirement labels, and hardware requirement labels. A schematic diagram of the four-level hierarchy and three-dimensional labels of the core product requirement library is shown below. Figure 2 As shown.

[0030] The methods for constructing an associated requirements library include: Acquire the display resource data, data resource data, and hardware resource data corresponding to each functional element, and construct a display requirement library, a data requirement library, and a hardware requirement library respectively. The display requirement library is used to store visualization components and their attributes, the data requirement library is used to store data table structures, data dictionaries, and interface protocols, and the hardware requirement library is used to store resource data such as specifications and models of hardware devices. The display requirement library, data requirement library, and hardware requirement library are associated with the corresponding functional elements through ID identifiers.

[0031] The product requirement library can also automatically classify and update functional elements based on the LDA topic modeling method. It regularly performs topic analysis on newly added project service data, business information, and user feedback data to identify potential functional categories and business scenarios, and generate corresponding functional elements. After being reviewed and confirmed by the system administrator, the functional elements are added to the product requirement library and the associated requirement library is updated synchronously to achieve continuous expansion and dynamic updates of the requirement library, so as to maintain consistency with actual business needs.

[0032] The generation of the functional meta list specifically includes: Receive the user's original requirement text: We need to build a visualization platform for offshore wind power projects that can display the real-time operating status of wind farms, including wind turbine operating data, meteorological monitoring data, and video surveillance footage.

[0033] By using the BERT pre-trained language model to perform syntactic analysis and intent recognition on the original requirement text, a hierarchical requirement semantic vector is constructed to complete deep semantic parsing. This can effectively identify ambiguous requirement expressions and automatically map them to the corresponding business domain function groups.

[0034] By using graph convolutional neural networks to learn the relationships between functional elements in the product demand database, a semantic similarity matrix between functional elements is generated, and functional combination recommendations are realized based on the relationships.

[0035] Based on semantic feature matching of demand, a set of candidate functional elements is obtained. The matching confidence of each candidate functional element is output, and combined with the semantic similarity matrix, suitable functional elements are intelligently pushed to users, including: The VIZ-101 wind turbine operation status dashboard is used to display key parameters such as power generation, wind speed, and blade angle of a single wind turbine and the entire field in real time. The VIZ-102 meteorological data real-time curve graph is used to display the real-time changes in meteorological elements such as wind speed, wind direction, temperature, and air pressure. The VIZ-103 video surveillance integrated component is used to connect IP cameras to achieve multi-screen split display and PTZ control. The DATA-201 wind turbine SCADA data access module provides a data interface with the wind turbine SCADA system. DATA-202 meteorological station data access is used to provide a data interface with wind measurement towers or meteorological stations; The HW-401 video surveillance equipment kit includes high-definition network cameras, NVR storage devices, etc.

[0036] The default confidence threshold is 0.7. The confidence level of this matching result meets the requirements, and there is no need to start the multi-turn dialogue engine.

[0037] Users confirm and verify the recommended set of functional elements. The system automatically extracts the project scale and environmental correlation features to support intelligent prediction of hardware quantity and finally generates a list of functional elements.

[0038] In other embodiments, the RoBERTa pre-trained language model can also be used to complete the syntactic analysis and intent recognition processing of the original requirement text.

[0039] The generation of the configuration scheme specifically includes: Based on the unique identifier of each functional element in the functional element list, the corresponding requirement information is obtained by performing related searches and aggregations in the data requirement library, display requirement library, and hardware requirement library.

[0040] Obtain the corresponding data access specifications and data table structure from the data requirements database: For SCADA data access of DATA-201 wind turbine, obtain data requirement information such as data point table, Modbus TCP / IP communication protocol, and 1-second acquisition frequency; For data access from the DATA-202 weather station, obtain data requirement information such as CSV / JSON data format and 4G / fiber optic transmission method.

[0041] Obtain the corresponding visual interface design specifications from the presentation requirements library: For the VIZ-101 wind turbine operation status dashboard, obtain display requirements information for a 1920×1080 large screen resolution, a refresh rate of ≥30fps, and various chart types such as dashboard / trend chart / bar chart; For the real-time curve chart of VIZ-102 meteorological data, obtain display requirements such as coordinate axis configuration, time axis sliding interaction, and data annotation functions; For the VIZ-103 video surveillance integrated component, obtain the H.264 / H.265 video stream decoding protocol and the 1 / 4 / 9 / 16 split-screen layout modes.

[0042] Retrieve the model specifications and matching parameters of the corresponding hardware devices from the hardware requirements database: For the HW-401 video surveillance equipment kit, obtain basic information such as the model numbers of the high-definition cameras, NVR storage devices, and core switches; Synchronous association call out HW Optional configuration parameters for related hardware such as the 402 large-screen display system, meteorological monitoring instrument, and industrial transmission gateway.

[0043] Based on historical project data, relevant features such as project scale, functional combination, and environmental scenario are extracted. The number of matching hardware devices for each type is automatically predicted using a random forest regression model. A multi-objective optimization function is constructed with hardware cost, performance, and scalability as optimization objectives. The basic hardware configuration is dynamically adjusted by combining a deep Q-network reinforcement learning strategy to generate initial hardware configurations of cost version, high-performance version, and balanced multiple versions.

[0044] By using TransE knowledge graph embedding to mine the compatibility constraint relationships between hardware devices, the initial hardware configuration is checked for constraints, hardware devices with compatibility conflicts are replaced, adaptation optimization is completed, and the final hardware requirements are obtained.

[0045] Finally, by integrating display requirements, data requirements, and optimized hardware requirements, multiple differentiated configuration solutions are output.

[0046] The generation of the digital service solution configuration data package specifically includes: The functional element list, display requirements, data requirements, hardware requirements, and hardware configuration information are uniformly sorted out and structurally integrated to gather multi-dimensional business and hardware information.

[0047] Based on the characteristics of market changes, an LSTM time series forecasting model is used to specifically calculate the market price changes of various hardware devices and their supporting cloud services, analyze the price rise and fall patterns in future cycles, and form a complete price fluctuation trend result.

[0048] Simultaneously read the budget constraints submitted by the user, and based on the obtained price fluctuation trends, flexibly formulate differentiated pricing strategies. Combine the project scale with preferential rules such as bulk discounts and early bird discounts for periodic cooperation, calculate the cost range of multiple demand configuration schemes, and determine a reasonable estimated price range.

[0049] Finally, the customized pricing rules, estimated cost ranges, and various differentiated requirement configuration schemes are linked and bound together, and then uniformly summarized and packaged to generate a complete and interconnected digital service solution configuration data package.

[0050] The generation of the requirements report specifically includes: Fill the digital service solution configuration data package into the preset standardized report template to automatically generate a structured "Offshore Wind Power Project Visualization Platform Construction Requirements Report". The flowchart of the requirements report generation is as follows: Figure 3 As shown, the report contains the following: Functional Requirements List: This list includes 3 functional groups, 6 functional elements, and their corresponding functional descriptions and quantity specifications. Supporting data requirements details: Specify the format, interface protocol, and data table structure of SCADA data and weather station data.

[0051] Visualized deliverables include: visual interface design diagrams, interaction instructions, and resolution requirements; Hardware configuration information: This section details the configuration of the video surveillance equipment kit and the optional large-screen display system, along with itemized pricing and the total cost. The total hardware cost is 125,000 yuan.

[0052] Product packaging specifically includes: The structured requirements report is productized and packaged into a digital product called "Offshore Wind Power Visualization Platform Standard Edition". This product has a standardized pricing and delivery model and is stored in the product catalog for direct access and adjustment in subsequent projects. Subsequent similar projects only need to adjust parameters such as the number of wind turbines and cameras based on this standardized product to quickly generate new requirements reports, realizing the productization and reuse of digital service solutions.

[0053] Figure 4 This is a schematic diagram of the structure of a digital service solution generation system based on a product demand database in an embodiment of the present invention. The device includes: The requirement library construction module is used to build product requirement libraries and related requirement libraries; The requirement parsing and matching module is used to obtain the original requirement text sent by the user, perform semantic parsing on the original requirement text to obtain requirement semantic features, match the candidate functional elements set from the pre-set product requirement library based on the requirement semantic features, and output the matching confidence of each candidate functional element. Based on the matching confidence, the candidate functional elements in the candidate functional element set are filtered and sorted to generate a recommended functional element set. The module obtains feedback data from the user on the recommended functional element set, verifies the recommended functional element set based on the feedback data, and generates a functional element list. The solution configuration and assembly module is used to perform related searches in a pre-set related requirement library based on the functional element list to obtain the corresponding display requirements, data requirements, and basic hardware requirements. It then uses a random forest regression model, multi-objective optimization functions, and knowledge graph embedding to optimize and adapt the basic hardware requirements, resulting in the final hardware requirements. The module aggregates the display requirements, data requirements, and hardware requirements to generate multiple differentiated requirement configuration schemes. Finally, it integrates these requirement configuration schemes in a structured manner and generates a digital service solution configuration data package through price fluctuation prediction and budget-adaptive pricing. The report generation module is used to populate the digital service solution configuration data package into a preset standardized report template to generate a structured requirements report.

[0054] This invention also provides a non-volatile computer storage medium storing computer-executable instructions, which are configured to implement the above-described method for generating digital service solutions based on a product requirements database.

[0055] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system and non-volatile computer storage medium embodiments are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0056] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0057] The above description is merely one or more embodiments of this specification and is not intended to limit this specification. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of this specification.

Claims

1. A method for generating digital service solutions based on a product demand database, characterized in that, Includes the following steps: The system obtains the original requirement text sent by the user, performs semantic parsing on the original requirement text to obtain requirement semantic features, matches a set of candidate functional elements from a pre-set product requirement database based on the requirement semantic features, outputs the matching confidence of each candidate functional element, filters and sorts the candidate functional elements in the candidate functional element set based on the matching confidence, generates a recommended functional element set, obtains feedback data from the user on the recommended functional element set, verifies the recommended functional element set based on the feedback data, and generates a functional element list. Based on the functional element list, a related search is performed in the pre-set related requirement library to obtain the corresponding display requirements, data requirements and basic hardware requirements. The basic hardware requirements are optimized and adapted using a random forest regression model, a multi-objective optimization function and knowledge graph embedding to obtain the final hardware requirements. The display requirements, data requirements and hardware requirements are aggregated to generate multiple sets of differentiated requirement configuration schemes. The aforementioned demand configuration schemes are structured and integrated, and a digital service solution configuration data package is generated by predicting price fluctuations and adjusting pricing according to budget. The configuration data package of the digital service solution is populated into a preset standardized report template to generate a structured requirements report.

2. The method for generating digital service solutions based on a product demand database according to claim 1, characterized in that, The method further includes: The structured requirements report is productized and packaged into a digital product with standardized pricing and delivery models, and the digital product is stored in the product catalog.

3. The method for generating digital service solutions based on a product demand database according to claim 1, characterized in that, The method further includes: Building a product requirements library specifically includes: The server acquires digital service capability data and, according to a pre-set data hierarchy structure, splits the digital service capability data. The pre-set data hierarchy structure includes at least a strategy layer, a business layer, a functional layer, and functional elements that are broken down layer by layer. Each functional element is associated with a unique three-dimensional label, which includes a display requirement label, a data requirement label, and a hardware requirement label. Building a related requirements library, specifically including: Obtain the display resource data, data resource data, and hardware resource data corresponding to each functional element, and construct a display requirement library, a data requirement library, and a hardware requirement library respectively. The display requirement library, the data requirement library, and the hardware requirement library are associated with the functional element through ID identification.

4. The method for generating digital service solutions based on a product demand database according to claim 3, characterized in that, Obtain user feedback data regarding the recommended feature set, and verify the recommended feature set based on the feedback data to generate a feature list, specifically including: A pre-trained language model is used to perform syntactic analysis and intent recognition on the original requirement text, and a hierarchical requirement semantic vector is constructed to obtain requirement semantic features. Based on graph convolutional neural networks, the association relationship between functional elements in the product requirement database is learned, and a semantic similarity matrix between functional elements is generated. Based on the semantic features of the requirements, a set of candidate functional elements is obtained by matching from the product requirement database, and the matching confidence of each candidate functional element is output. The candidate functional element set is filtered and sorted according to the matching confidence to generate a recommended functional element set. Based on the semantic similarity matrix, the functional elements in the recommended functional element set are combined and recommended. When the matching confidence level is lower than a preset threshold, a multi-round interaction process is initiated, and the matching result is iteratively updated based on the response data fed back by the user until a matching result with high confidence level is obtained. The recommended feature set is verified based on the high-confidence matching results to generate a feature list.

5. The method for generating digital service solutions based on a product demand database according to claim 1, characterized in that, The aforementioned display requirements, data requirements, and hardware requirements are aggregated to generate multiple differentiated requirement configuration schemes, specifically including: Based on the functional element list, perform related searches and requirement matching in the related requirement library to obtain the corresponding display requirements, data requirements and basic hardware requirements. Based on the basic hardware requirements, and combined with historical project data, the project scale and environmental factors are extracted as correlation features, and a random forest regression model is constructed to predict the number of various hardware devices. Using the cost, performance, and scalability of hardware devices as optimization objectives, a multi-objective optimization function is constructed. Combined with the predicted number of hardware devices, the hardware configuration corresponding to the basic hardware requirements is dynamically adjusted to generate the initial hardware configuration. The compatibility constraint relationships between hardware devices are mined using knowledge graph embedding. The initial hardware configuration is checked for compatibility constraints, and hardware configurations that do not meet the compatibility constraint requirements are filtered out. Hardware configurations with compatibility conflicts are replaced and adapted to obtain the final hardware requirements. The aforementioned display requirements, data requirements, and hardware requirements are aggregated to generate multiple differentiated requirement configuration schemes.

6. The method for generating digital service solutions based on a product demand database according to claim 5, characterized in that, The display requirements include at least the requirements for visualization components, interface design specifications, and resolution; and / or The data requirements include at least data interface protocol requirements, data table structure requirements, data acquisition frequency requirements, and data format requirements; and / or The hardware requirements include at least the hardware device model requirements, device specification requirements, device unit price requirements, device quantity requirements, and total device price requirements.

7. The method for generating digital service solutions based on a product demand database according to claim 1, characterized in that, The aforementioned demand configuration schemes are structured and integrated, and a digital service solution configuration data package is generated through price fluctuation prediction and budget-adaptive pricing. Specifically, this includes: A time series forecasting model is used to predict the prices of various hardware devices and their associated cloud services, and to obtain price fluctuation trends. Obtain the user's budget data, combine it with the price fluctuation trend to generate a pricing strategy, and calculate the estimated price range for each demand configuration scheme; The pricing strategy and estimated price range are linked with the demand configuration plan to generate a digital service solution configuration data package.

8. The method for generating digital service solutions based on a product demand database according to claim 1, characterized in that, The structured requirements report includes a list of functional requirements, detailed supporting data requirements, visualized deliverables, and hardware configuration information. The functional requirements list shall include at least the functional elements and their corresponding quantity parameters; The detailed requirements for the supporting data include at least the data interface protocol, data table structure, and data collection frequency. The visualized delivery information includes at least the interface design specifications, chart types, and interaction methods. The hardware configuration information includes at least a list of devices, the quantity of devices, the unit price of devices, and the total price of devices.

9. A digital service solution generation system based on a product requirements database, characterized in that, The system is used to implement the digital service solution generation method based on a product demand database as described in any one of claims 1-8, including: The requirement library construction module is used to build product requirement libraries and related requirement libraries; The requirement parsing and matching module is used to obtain the original requirement text sent by the user, perform semantic parsing on the original requirement text to obtain requirement semantic features, match the candidate functional elements set from the pre-set product requirement library based on the requirement semantic features, and output the matching confidence of each candidate functional element. Based on the matching confidence, the candidate functional elements in the candidate functional element set are filtered and sorted to generate a recommended functional element set. The module obtains feedback data from the user on the recommended functional element set, verifies the recommended functional element set based on the feedback data, and generates a functional element list. The solution configuration and assembly module is used to perform related searches in a pre-set related requirement library based on the functional element list to obtain the corresponding display requirements, data requirements, and basic hardware requirements. It then uses a random forest regression model, multi-objective optimization functions, and knowledge graph embedding to optimize and adapt the basic hardware requirements, resulting in the final hardware requirements. The module aggregates the display requirements, data requirements, and hardware requirements to generate multiple differentiated requirement configuration schemes. Finally, it integrates these requirement configuration schemes in a structured manner and generates a digital service solution configuration data package through price fluctuation prediction and budget-adaptive pricing. The report generation module is used to populate the digital service solution configuration data package into a preset standardized report template to generate a structured requirements report.

10. A non-volatile computer storage medium, characterized in that, The device stores computer-executable instructions configured to implement the digital service solution generation method based on a product requirements database as described in any one of claims 1-8.

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