An interactive interface generation method and device, computer equipment and a storage medium

Abstract

The application relates to the technical field of artificial intelligence, and discloses an interactive interface generation method and device, computer equipment and a storage medium, the method comprising the following steps: in response to a user input statement, structurally analyzing the user input statement to obtain user demand information; generating an interface configuration scheme based on the user demand information and a preset knowledge graph; selecting an interface component in a preset interface component library according to the interface configuration scheme; performing parameter configuration on the selected interface component based on the user demand information; and assembling the interface component after the parameter configuration is completed to generate an interactive interface. The application can be applied to a financial technology, medical health and pension business system platform, and solves the technical problem that an existing technology cannot quickly and efficiently generate a corresponding interface for a user problem during human-computer interaction.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology, and specifically to an interactive interface generation method, apparatus, computer device, and storage medium. Background Technology

[0002] Human-Computer Interaction Interface (HCI Interface) is a bridge for information exchange and operation between users and computer systems. Its core goal is to enable users to complete target tasks efficiently, naturally, and pleasantly.

[0003] In the fintech field, users can quickly obtain information about their funds through human-computer interfaces. However, current financial institutions' human-computer interfaces generally adopt traditional static page designs. Their front-end interfaces typically use fixed page structures and navigation logic, requiring users to click through pre-defined paths to obtain the information they need. For example, if a customer wants to view the historical returns of a fund, they need to navigate through multiple levels such as "Wealth Management" -> "Funds" -> "My Funds" -> "Details Page" -> "Historical Returns," resulting in low interaction efficiency. For ordinary users unfamiliar with financial products, the complex menu structure and technical terminology increase the barrier to entry. Moreover, existing financial data dashboards usually have fixed time dimensions (such as daily, weekly, and monthly) and data indicators. If users need to view specific time periods or custom indicator combinations, they often need to access advanced settings or filtering functions, which is complex and provides a fragmented user experience. For example, if a customer wants to compare and analyze "the difference between transaction volume on weekdays and holidays in the last three months," existing systems struggle to quickly respond to such non-standardized query needs.

[0004] In the healthcare field, users can check the progress of their medical insurance claims through human-computer interaction interfaces. However, most of these interfaces remain at a simple question-and-answer level, failing to truly understand the user's intent and generate a corresponding interactive interface. When users inquire about the progress of their insurance claims, the system can only return textual answers, rather than directly displaying a visual flowchart of the claims process and the current status, resulting in low information transmission efficiency and difficulty in user comprehension. Summary of the Invention

[0005] The purpose of this invention is to overcome the above-mentioned technical deficiencies and provide an interactive interface generation method, device, computer equipment and storage medium applicable to financial technology, healthcare or other related technical fields, solving the technical problem in the prior art that it is impossible to quickly and efficiently generate corresponding interfaces for user questions during human-computer interaction.

[0006] To achieve the above-mentioned technical objectives, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a method for generating an interactive interface, comprising the following steps: In response to user input statements, the user input statements are parsed in a structured manner to obtain user demand information; Based on the user needs information and the preset knowledge graph, an interface configuration scheme is generated; According to the interface configuration scheme, select interface components from the preset interface component library; Based on the user demand information, the parameters of the selected interface components are configured. Assemble the interface components with the parameters configured to generate an interactive interface.

[0008] Secondly, the present invention also provides an interactive interface generation apparatus, comprising: The parsing module is used to respond to user input statements by performing structured parsing on the user input statements to obtain user requirement information; The solution generation module is used to generate an interface configuration solution based on the user requirement information and the preset knowledge graph; The component selection module is used to select interface components from a preset interface component library according to the interface configuration scheme. The component configuration module is used to configure the parameters of the selected interface components based on the user requirement information. The interface generation module is used to assemble the interface components after the parameters are configured to generate an interactive interface.

[0009] Thirdly, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the steps of the interactive interface generation method described above.

[0010] Fourthly, the present invention also provides a computer-readable storage medium storing computer-readable instructions, which, when executed by a processor, implement the steps of the interactive interface generation method described above.

[0011] Compared with existing technologies, the interactive interface generation method, apparatus, computer equipment, and storage medium provided by this invention first respond to user input statements by performing structured parsing of the user input statements to obtain user demand information; then, based on the user demand information and a preset knowledge graph, an interface configuration scheme is generated; subsequently, according to the interface configuration scheme, interface components are selected from a preset interface component library; then, based on the user demand information, the selected interface components are parameter-configured; finally, the parameter-configured interface components are assembled to generate the interactive interface. This invention introduces the natural language understanding capabilities of a large model to construct an intent recognition model specifically for the financial field. When a user expresses their needs through dialogue, the system no longer directs to a fixed page but instead analyzes the user's intent in real time, identifies key elements (such as time range, data dimensions, business scenarios, etc.), and dynamically generates the most suitable interactive interface. Users do not need to learn complex menu structures and operation processes; they can directly access the target information through natural dialogue. Especially for ordinary customers with insufficient financial knowledge, this lowers the barrier to entry and enables them to quickly obtain the services they need. Attached Figure Description

[0012] To more clearly illustrate the solutions in this invention, the accompanying drawings used in the description of the embodiments of this invention will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0013] Figure 1 This is an exemplary system architecture diagram in which the present invention can be applied; Figure 2 This is a flowchart of an embodiment of the interactive interface generation method according to the present invention; Figure 3 This is a schematic diagram of a structure of an embodiment of the interactive interface generation device according to the present invention; Figure 4 This is a schematic diagram of the structure of an embodiment of a computer device according to the present invention; Figure 5 This is a schematic diagram of another embodiment of the computer device according to the present invention. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0015] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0016] To enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0017] The AI-based interactive interface generation method provided in this invention can be applied to, for example... Figure 1 In this application environment, the client communicates with the server via a network. The server responds to user input by performing structured parsing to obtain user requirement information; then, based on this user requirement information and a pre-defined knowledge graph, it generates an interface configuration scheme; subsequently, according to the interface configuration scheme, it selects interface components from a pre-defined interface component library; then, based on the user requirement information, it configures the parameters of the selected interface components; finally, it assembles the parameter-configured interface components to generate an interactive interface. This invention introduces the natural language understanding capabilities of a large model to construct a dedicated intent recognition model for the financial field. When a user expresses their needs through dialogue, the system no longer directs them to a fixed page, but instead analyzes the user's intent in real time, identifies key elements (such as time range, data dimensions, business scenarios, etc.), and dynamically generates the most suitable interactive interface. Users do not need to learn complex menu structures and operation processes; they can directly access the target information through natural dialogue. This lowers the barrier to entry, especially for ordinary customers with insufficient financial knowledge, enabling them to quickly obtain the services they need. The client can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented using a dedicated server or a server cluster consisting of multiple servers. The present invention will now be described in detail through specific embodiments.

[0018] Please see Figure 2 , Figure 2 A flowchart of an embodiment of the interactive interface generation method according to the present invention is shown. The interactive interface generation method can be applied to business query scenarios in financial scenarios or insurance claim progress query scenarios in medical scenarios, including steps S100 to S500.

[0019] S100: In response to the user input statement, perform structured parsing on the user input statement to obtain user requirement information.

[0020] In this embodiment, user input statements submitted through various channels are acquired, such as statements entered by the user via a mobile app or webpage. The user input statement is the query entered by the user, reflecting the user's intent. The user input statement can be either text or voice information, without limitation. It should be noted that when the user inputs a statement via voice, the system can automatically convert the voice information into text information for easier information extraction.

[0021] User input statements could include phrases like "I want to check the fund's returns over the past three months, focusing on volatility"; or voice inquiries from the user's client such as "How is my claim progressing?" After receiving the user input statements, the server performs structured parsing to extract the user's needs and related information.

[0022] For example, taking a fund query scenario, a user asks through the client, "I want to see the fund returns over the past three months, with a focus on volatility." The server uses a large model to identify the user's needs, such as the business scenario, time range, and key metrics. For instance, the identified business scenario is fund return analysis, the time range is the past three months, and the key metrics are return rate and volatility.

[0023] Taking medical insurance claims as an example, when a user asks "How is my insurance claim progress?" through the client, the server uses a large model to identify the statement, and the identified business scenario is insurance claims, with the focus metric being the claim progress.

[0024] S200. Based on the user demand information and the preset knowledge graph, generate an interface configuration scheme.

[0025] In this embodiment, the user demand information may include one or more parameters such as business scenario, attention indicators, and time indicators. Among them, attention indicators are the user's intent information, that is, the data that the user wants to obtain. The business scenario is the scenario information that the user wants to query, such as fund query scenario, insurance claim progress query scenario, etc. This disclosure matches the user demand information in a preset knowledge graph to obtain the matching data corresponding to the user demand information. Then, the interface configuration scheme corresponding to the user demand information is obtained through the matching data, so that the interface can be quickly configured according to the interface configuration scheme.

[0026] A knowledge graph is a semantic network that describes entities and their relationships in the physical world in a structured form. It is a core infrastructure for artificial intelligence to achieve cognitive intelligence. It integrates fragmented knowledge into a network of connections through a graph structure, supporting machine understanding, reasoning, and decision-making. Entities are objects in the real world, such as people, places, organizations, concepts, and funds. For example, when generating interactive interfaces in a financial scenario, a pre-built financial knowledge graph can be used to generate the interface configuration scheme.

[0027] S300. According to the interface configuration scheme, select interface components from the preset interface component library.

[0028] In this embodiment, once the interface configuration scheme is obtained, corresponding interface components can be selected according to the scheme, and then an interactive interface can be formed by combining these components. The interface component library is pre-built and can be updated in real time. Optionally, the interface component library includes at least basic data components, analytical components, process components, and intelligent recommendation components. For example, basic data components may include account balance cards, transaction history tables, asset distribution pie charts, etc. Analytical components may include revenue attribution analysis, risk assessment radar charts, market comparisons, etc. Process components may include business processing progress bars, approval flowcharts, operation guidance steps, etc. Intelligent recommendation components may include product recommendation cards, risk warning banners, personalized suggestion lists, etc.

[0029] In the traditional model, every new business scenario or function adjustment requires the development of new pages and navigation logic. This disclosure, through componentization and intelligent generation mechanisms, allows new scenarios to be developed by simply expanding the interface component library and configuration rules, without requiring large-scale front-end modifications, thus significantly reducing development and maintenance costs.

[0030] S400. Based on the user requirement information, configure the parameters of the selected interface components.

[0031] In this embodiment, after selecting an interface component, the parameters of the interface component can be configured according to the user's specific situation, thereby obtaining the interface component corresponding to the user.

[0032] For example, when querying an account balance, the user's account balance data is bound to the selected account balance card, and then the account balance card is configured. When querying fund volatility, the fund volatility chart can be configured according to the current fund volatility to obtain an interface component that reflects the specific fund volatility.

[0033] S500: Assemble the interface components with the parameters configured to generate an interactive interface.

[0034] In this embodiment, after the parameters of the interface components are configured, the interface rendering engine can be invoked to assemble and generate a personalized front-end page in real time. This allows for the direct generation of a completely personalized information architecture and display content based on user input.

[0035] It should be noted that, after generating the interactive interface, this embodiment of the disclosure can record the user's interface preferences for subsequent interaction optimization. For example, the system can record the user's layout preferences, color preferences, font preferences, etc. This includes recording the user's preferences for the arrangement order and position of interface elements (such as buttons, menus, text boxes, etc.), and recording the user's preferences for window size. For example, some users may prefer to place frequently used function buttons at the top of the interface, while others may prefer them at the bottom. Recording the user's window size preference allows for automatic adjustment to the user's preferred size the next time the application is opened. Recording the user's selected font type, such as SimSun, Microsoft YaHei, Arial, etc., improves user viewing convenience. Recording the user's font size preference allows for automatic adjustment of the font size in subsequent interactions, improving readability.

[0036] In this embodiment of the invention, the system first responds to user input by performing structured parsing to obtain user requirement information. Then, based on the user requirement information and a pre-defined knowledge graph, an interface configuration scheme is generated. Next, according to the interface configuration scheme, interface components are selected from a pre-defined interface component library. Then, based on the user requirement information, the selected interface components are parameter-configured. Finally, the parameter-configured interface components are assembled to generate an interactive interface. This invention introduces the natural language understanding capabilities of a large-scale model to construct a dedicated intent recognition model for the financial field. The entire system process begins with user dialogue input, proceeds through large-scale model intent parsing, identifies business scenarios, extracts key parameters, queries the financial knowledge graph, generates an interface configuration scheme, selects interface components, calls data services, and finally renders a personalized interface. After user interaction feedback, the system determines whether adjustments are needed. If adjustments are required, it returns to the intent parsing step; otherwise, it records user preferences and updates the knowledge base. When a user expresses a need through dialogue, the system no longer directs to a fixed page but instead parses the user's intent in real time, identifies key elements (such as time range, data dimensions, business scenarios, etc.), and dynamically generates the most suitable interactive interface. Users don't need to learn complex menu structures and operating procedures; they can directly access the information they need through natural dialogue. This lowers the barrier to entry, especially for ordinary customers with limited financial knowledge, allowing them to quickly obtain the services they require.

[0037] In some embodiments, step S100 includes: Obtain user input statements and perform word segmentation on the user input statements; The user input statement after word segmentation is input into a pre-built large model to extract features from the user input statement; Based on the extracted features, user demand information is obtained.

[0038] In this embodiment, a large model can be used to analyze user input statements and extract features. The large model can be an external large model API or a finely tuned large model tailored to a specific task. In scenarios with low time requirements, an external large model API can be used; in scenarios with high time requirements, a finely tuned large model can be used. Whether the time requirement is high or low depends on the product definition. High real-time requirements naturally result in high time requirements. For example, in a problem-solving scenario, where the product definition requires real-time feedback from the intelligent dialogue system, this is a high-time-requirement scenario.

[0039] For example, the large model can be Agent / LLM. When it receives user input, it first performs word segmentation on the user input, dividing the input into sub-words or word units and mapping them into vectors. Then, the corresponding mapped vectors are input to Agent / LLM for the large model to analyze and extract features. Finally, user demand information is obtained based on the features.

[0040] Word segmentation involves dividing continuous text into meaningful units (such as words, subwords, or characters) to provide structured input for subsequent large-scale models. For example, when a user inputs "I want to see the fund's returns over the past three months, focusing on volatility," word segmentation transforms the input into several words such as "I want to see," "over the past three months," "fund," "returns," "focus on," and "rate of return." This allows the subsequent large-scale model to better capture the user's intent and extract the desired information from the input.

[0041] In some embodiments, step S200 includes: Based on the preset knowledge graph, obtain the association information between the various entity data in the user demand information; Based on the aforementioned association information, an interface configuration scheme is generated.

[0042] In this embodiment, the association information of each entity data in the user's demand information is first obtained through a pre-constructed knowledge graph. For example, if the user input statement is "I want to see the fund returns in the last three months, focusing on volatility", then based on the user demand information in the user input statement, including the business scenario (fund returns), the analysis time range (last three months), and the indicators to be focused on (yield, volatility), the financial knowledge graph can match the associated information of fund returns as fund return data, the associated information of the analysis time range as the last three months, and the indicators to be focused on as yield and volatility information. Then, an interface configuration scheme can be generated through a pre-set display method. For example, if the pre-set display method is trend chart + indicator cards, then the interface configuration scheme generated based on this is: generating a dedicated dashboard containing a three-month yield trend chart, a volatility heatmap, and key indicator comparison cards.

[0043] In some embodiments, step S300 includes: Based on the business scenario corresponding to the interface configuration scheme, select the corresponding basic data interface component from the interface component library; Based on the relevant metrics in the interface configuration scheme, select the corresponding data analysis interface components from the interface component library.

[0044] In this embodiment, UI components are the basic elements for building the user interface. They are combined and nested to form a complete interactive interface. The design of UI components directly affects user experience, development efficiency, and system maintainability. UI components are independent, reusable UI modules that encapsulate specific functions or visual styles, and are combined to achieve complex interfaces. When selecting UI components, basic data UI components are first selected based on the business scenario. For example, in the account balance query scenario, the account balance card UI component can be selected. Then, data analysis UI components are selected based on the user's focus indicators. The data analysis UI components can include analysis components and process components. For example, in the balance query scenario, the balance change analysis component can be selected. By selecting multiple interfaces and assembling them, an interactive interface corresponding to the user's required information can be obtained.

[0045] In order to increase the diversity of the interactive interface, this public interface component library also stores intelligent recommendation components, which can not only display user needs but also intelligently recommend services.

[0046] It should be noted that each UI component possesses adaptive layout capabilities, a permission verification mechanism, and real-time data binding functionality. Adaptive layout means the UI component automatically adjusts its display size based on device type and screen size. The permission verification mechanism allows the UI component to automatically verify whether a user has permission to view specific data. Real-time data binding means the UI component is integrated with the backend financial core system, enabling the display of real-time data.

[0047] In some embodiments, step S400 includes: Based on the user demand information, search the preset database for the scene parameters corresponding to the user demand information; Based on the scene parameters, the selected interface components are configured.

[0048] In this embodiment, the preset database stores various financial data or insurance claim data. When a client needs to query its own account information, it can configure the selected interface components by searching the corresponding user account data in the database. When a client needs to query current market conditions, it can configure the selected interface components by searching the corresponding market condition data in the database. After the interface components are configured with parameters, they can be assembled to form a client-specific interactive interface.

[0049] For example, when a user asks, "I want to see the fund's returns over the past three months, with a focus on volatility," the system identifies the business scenario as fund return analysis, the time frame as the past three months, and the key metrics as return and volatility. The system then retrieves the user's fund return and volatility data for the past three months from the database and configures the parameters for interface components such as the three-month return trend chart, volatility heatmap, and key indicator comparison cards.

[0050] In some embodiments, step S500 includes: Based on the built-in rules of the interface components, determine whether the client corresponding to the user input statement has the calling permission; Provided the client has the necessary access permissions, the layout size of the interface components is adjusted based on the client's screen size. Based on a preset rendering tool, the adjusted interface components are assembled to generate an interactive interface.

[0051] In this embodiment, to prevent unauthorized users from accessing unauthorized data, the interface components are configured with built-in rules that reflect whether a user has permission to access data. Therefore, permission verification is required first when assembling the interactive interface. After successful permission verification, the layout size of the interface components is adjusted according to the user's screen size, and finally, the interface components are assembled using a preset rendering tool.

[0052] During interface rendering, the interface can be assembled using an existing interface rendering engine. The interface rendering engine is the core component responsible for converting application interface data into visual images. Its core functions include data parsing, graphics rendering, performance optimization, and cross-platform adaptation, and it is widely used in games, mobile applications, web pages, and low-code development platforms. For example, the server receives interface description data from the application, such as layout structure, style information, and interaction logic. This data is parsed and processed, converting it into an internal representation that the rendering engine can understand. Based on the parsed data, the various elements of the interface, such as buttons, text, and images, are drawn on the screen. Various graphic effects, such as shadows, gradients, and transparency, can be configured for each element to enhance the visual appeal of the interface. Various techniques are employed to optimize rendering performance, such as reducing unnecessary redraws and using hardware acceleration. This ensures that the interface runs smoothly on various devices, providing a good user experience.

[0053] The UI rendering engine supports operation on different operating systems and devices, such as Windows, macOS, iOS, and Android. It can adaptively adjust to the characteristics of different platforms to ensure that the interface displays correctly on various devices.

[0054] In a feasible implementation, a rendering engine typically employs a rendering pipeline to process data and generate images. The rendering pipeline includes multiple stages, such as vertex processing, primitive assembly, and pixel processing, each using specific algorithms and computational steps to process data and generate intermediate results. The rendering engine can also interact with the graphics card using graphics APIs (such as OpenGL, DirectX, and Vulkan). These APIs provide interfaces for drawing graphics, processing textures, and applying lighting, enabling the rendering engine to leverage the powerful computing capabilities of the graphics card to accelerate the rendering process. Furthermore, UI rendering engines can use shaders to color UI components. Shaders are small programs running on the graphics card used to handle calculations related to lighting, color, and other visual effects. Rendering engines typically use shaders to implement various graphical effects, such as shadows, reflections, and refractions.

[0055] In some embodiments, step S400 is followed by: Interact with the client to obtain supplementary information from the client's feedback; Based on the supplementary information, the interactive interface is adjusted, and the adjusted interactive interface is fed back to the client.

[0056] In this embodiment, unlike the one-time information presentation method of traditional systems, a progressive interface optimization mode can be formed through multi-turn dialogue. Specifically, this embodiment supports the gradual refinement and optimization of interface content through multi-turn dialogue, realizing a human-computer collaborative interface construction process. After generating the basic interface framework based on the first round of dialogue, the server will proactively ask the client whether the user needs adjustments, such as asking "Do you need to add comparisons with similar products?". Then, based on the user's feedback, interface components are dynamically added, deleted, or adjusted, thereby better presenting the interactive interface according to user needs.

[0057] For example, taking an insurance claim scenario, the initial dialogue from the client is "How is my claim progress?" The server first generates a basic progress bar interface based on the initial dialogue, and then actively guides the client to optimize the interface. For example, the server guides the client to ask "What other materials do I need to provide?", at which point the server will dynamically add a materials list module to the interface. The server guides the client to ask "When is the payment expected?", at which point the server will add a timeline and predicted payment date module to the interface. The server guides the client to ask "Can I see the payment details?", at which point the server will expand the cost breakdown table on the interface.

[0058] This disclosure determines whether adjustments are needed after interacting with and receiving feedback from users. If adjustments are needed, it returns to the intent parsing step; otherwise, it records user preferences and updates the knowledge base. This can increase the personalization of the generated interactive interface and more accurately obtain user needs, making the presented interactive interface more in line with user requirements.

[0059] The technical solution provided by this invention first responds to user input statements by performing structured parsing of the user input statements to obtain user requirement information; then, based on the user requirement information and a preset knowledge graph, an interface configuration scheme is generated; next, according to the interface configuration scheme, interface components are selected from a preset interface component library; then, based on the user requirement information, the selected interface components are parameter-configured; finally, the parameter-configured interface components are assembled to generate an interactive interface. Compared with existing technologies, this invention has the following advantages: (1) Significantly improved user experience: Users do not need to learn complex menu structures and operation processes; they can directly access the target information through natural dialogue. In particular, it lowers the usage threshold for ordinary customers with insufficient financial knowledge, enabling them to quickly obtain the services they need. Taking the inquiry of wealth management products as an example, a task that originally required 5-8 steps can now be completed in 2-3 rounds of dialogue, improving operational efficiency by more than 60%.

[0060] (2) Achieving truly personalized service: The system dynamically generates an interface based on each user's actual needs, risk preferences, and historical behavior, so different users see a completely personalized information architecture and content. This deep personalization can improve customer satisfaction and business conversion rate, which is especially important for wealth management scenarios for high-net-worth clients.

[0061] (3) Enhance the intelligence level of financial services: Deeply integrate the understanding and reasoning capabilities of large models with financial services, so that intelligent customer service can evolve from "passive question answering" to "proactive service". The system can not only understand user questions, but also predict needs and proactively recommend relevant functions and products, thus building a more intelligent financial service ecosystem.

[0062] (4) Reduce system maintenance costs: In the traditional model, every time a new business scenario is added or a function is adjusted, a new page and navigation logic need to be developed. This disclosure uses a componentization and intelligent generation mechanism, so that new scenarios only need to expand the component library and configuration rules, without large-scale front-end modification, and the development and maintenance costs are significantly reduced.

[0063] (5) Enhance risk management capabilities: While dynamically generating the interface, the system can automatically add risk warning components based on the user's risk level and the product's risk attributes to achieve precise suitability management. For example, when showing high-risk products to customers with low risk tolerance, the interface will automatically highlight risk warning information to help financial institutions fulfill their compliance obligations.

[0064] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0065] Another embodiment of the present invention provides an interactive interface generation apparatus, which corresponds one-to-one with the interactive interface generation method in the above embodiments. Please refer to... Figure 3 The interactive interface generation device includes a parsing module 11, a scheme generation module 12, a component selection module 13, a component configuration module 14, and an interface generation module 15. Detailed descriptions of each functional module are as follows: The parsing module 11 is used to respond to the user input statement, perform structured parsing on the user input statement, and obtain user requirement information.

[0066] The scheme generation module 12 is used to generate an interface configuration scheme based on the user requirement information and the preset knowledge graph.

[0067] The component selection module 13 is used to select interface components from a preset interface component library according to the interface configuration scheme.

[0068] The component configuration module 14 is used to configure the parameters of the selected interface components based on the user requirement information.

[0069] The interface generation module 15 is used to assemble the interface components with the parameters configured to generate an interactive interface.

[0070] In some embodiments, the scheme generation module 12 is specifically used for: Based on the preset knowledge graph, obtain the association information between the various entity data in the user demand information; Based on the aforementioned association information, an interface configuration scheme is generated.

[0071] In some embodiments, the component selection module 13 is specifically used for: Based on the business scenario corresponding to the interface configuration scheme, select the corresponding basic data interface component from the interface component library; Based on the relevant metrics in the interface configuration scheme, select the corresponding data analysis interface components from the interface component library.

[0072] In some embodiments, the component configuration module 14 is specifically used for: Based on the user demand information, search the preset database for the scene parameters corresponding to the user demand information; Based on the scene parameters, the selected interface components are configured.

[0073] In some embodiments, the interface generation module 15 is specifically used for: Based on the built-in rules of the interface components, determine whether the client corresponding to the user input statement has the calling permission; Provided the client has the necessary access permissions, the layout size of the interface components is adjusted based on the client's screen size. Based on a preset rendering tool, the adjusted interface components are assembled to generate an interactive interface.

[0074] In some embodiments, the parsing module 11 is specifically used for: Obtain user input statements and perform word segmentation on the user input statements; The user input statement after word segmentation is input into a pre-built large model to extract features from the user input statement; Based on the extracted features, user demand information is obtained.

[0075] In some embodiments, the interactive interface generation device further includes an adjustment module, configured to: Interact with the client to obtain supplementary information from the client's feedback; Based on the supplementary information, the interactive interface is adjusted, and the adjusted interactive interface is fed back to the client.

[0076] In this embodiment of the invention, firstly, in response to user input, the system performs structured parsing of the user input to obtain user demand information; then, based on the user demand information and a preset knowledge graph, it generates an interface configuration scheme; next, according to the interface configuration scheme, it selects interface components from a preset interface component library; then, based on the user demand information, it configures the parameters of the selected interface components; finally, it assembles the parameter-configured interface components to generate an interactive interface. This invention introduces the natural language understanding capabilities of a large model to construct an intent recognition model specifically for the financial field. When a user expresses their needs through dialogue, the system no longer directs them to a fixed page, but instead analyzes the user's intent in real time, identifies key elements (such as time range, data dimensions, business scenarios, etc.), and dynamically generates the most suitable interactive interface. Users do not need to learn complex menu structures and operation processes; they can directly access the target information through natural dialogue. This significantly lowers the barrier to entry for ordinary customers with insufficient financial knowledge, enabling them to quickly obtain the services they need.

[0077] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing related hardware through computer-readable instructions. These computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0078] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0079] Specific limitations regarding the interactive interface generation device can be found in the limitations of the interactive interface generation method described above, and will not be repeated here. Each module in the aforementioned interactive interface generation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in the computer device in hardware form, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0080] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When the computer program is executed by the processor, it implements the functions or steps of a server-side method for generating an artificial intelligence-based interactive interface.

[0081] In one embodiment, a computer device is provided, which may be a client, and its internal structure diagram may be as follows: Figure 5As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with an external server via a network connection. When the computer program is executed by the processor, it implements the client-side functions or steps of an interactive interface generation method.

[0082] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps: In response to user input statements, the user input statements are parsed in a structured manner to obtain user demand information; Based on the user needs information and the preset knowledge graph, an interface configuration scheme is generated; According to the interface configuration scheme, select interface components from the preset interface component library; Based on the user demand information, the parameters of the selected interface components are configured. Assemble the interface components with the parameters configured to generate an interactive interface.

[0083] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor: In response to user input statements, the user input statements are parsed in a structured manner to obtain user demand information; Based on the user needs information and the preset knowledge graph, an interface configuration scheme is generated; According to the interface configuration scheme, select interface components from the preset interface component library; Based on the user demand information, the parameters of the selected interface components are configured. Assemble the interface components with the parameters configured to generate an interactive interface.

[0084] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions on the server side and client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0085] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0086] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0087] In summary, the interactive interface generation method, apparatus, computer device, and storage medium provided by this invention first respond to user input statements by performing structured parsing of the user input statements to obtain user demand information; then, based on the user demand information and a preset knowledge graph, an interface configuration scheme is generated; subsequently, according to the interface configuration scheme, interface components are selected from a preset interface component library; then, based on the user demand information, the selected interface components are parameter-configured; finally, the parameter-configured interface components are assembled to generate an interactive interface. This invention introduces the natural language understanding capabilities of a large model to construct an intent recognition model specifically for the financial field. When a user expresses their needs through dialogue, the system no longer directs to a fixed page but instead analyzes the user's intent in real time, identifies key elements (such as time range, data dimensions, business scenarios, etc.), and dynamically generates the most suitable interactive interface. Users do not need to learn complex menu structures and operation processes; they can directly access the target information through natural dialogue. Especially for ordinary customers with insufficient financial knowledge, this lowers the barrier to entry and enables them to quickly obtain the services they need.

[0088] It should be noted that if any software tools or components not belonging to our company appear in the embodiments of this application, they are merely for illustrative purposes and do not represent actual use.

[0089] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for generating an interactive interface, characterized in that, Includes the following steps: In response to user input statements, the user input statements are parsed in a structured manner to obtain user demand information; Based on the user needs information and the preset knowledge graph, an interface configuration scheme is generated; According to the interface configuration scheme, select interface components from the preset interface component library; Based on the user demand information, the parameters of the selected interface components are configured. Assemble the interface components with the parameters configured to generate an interactive interface.

2. The interactive interface generation method according to claim 1, characterized in that, The step of generating an interface configuration scheme based on the user demand information and a preset knowledge graph includes: Based on the preset knowledge graph, obtain the association information between the various entity data in the user demand information; Based on the aforementioned association information, an interface configuration scheme is generated.

3. The interactive interface generation method according to claim 1, characterized in that, The step of selecting interface components from a preset interface component library according to the interface configuration scheme includes: Based on the business scenario corresponding to the interface configuration scheme, select the corresponding basic data interface component from the interface component library; Based on the relevant metrics in the interface configuration scheme, select the corresponding data analysis interface components from the interface component library.

4. The interactive interface generation method according to claim 1, characterized in that, The step of configuring parameters for the selected interface components based on the user requirement information includes: Based on the user demand information, search the preset database for the scene parameters corresponding to the user demand information; Based on the scene parameters, the selected interface components are configured.

5. The interactive interface generation method according to claim 1, characterized in that, Assembling the interface components after configuring the parameters to generate an interactive interface includes: Based on the built-in rules of the interface components, determine whether the client corresponding to the user input statement has the calling permission; Provided the client has the necessary access permissions, the layout size of the interface components is adjusted based on the client's screen size. Based on a preset rendering tool, the adjusted interface components are assembled to generate an interactive interface.

6. The interactive interface generation method according to any one of claims 1 to 5, characterized in that, The step of responding to user input statements by performing structured parsing of the user input statements to obtain user request information includes: Obtain user input statements and perform word segmentation on the user input statements; The user input statement after word segmentation is input into a pre-built large model to extract features from the user input statement; Based on the extracted features, user demand information is obtained.

7. The interactive interface generation method according to any one of claims 1 to 5, characterized in that, After assembling the interface components with the configured parameters to generate the interactive interface, the process includes: Interact with the client to obtain supplementary information from the client's feedback; Based on the supplementary information, the interactive interface is adjusted, and the adjusted interactive interface is fed back to the client.

8. An interactive interface generation device, characterized in that, include: The parsing module is used to respond to user input statements by performing structured parsing on the user input statements to obtain user requirement information; The solution generation module is used to generate an interface configuration solution based on the user requirement information and the preset knowledge graph; The component selection module is used to select interface components from a preset interface component library according to the interface configuration scheme. The component configuration module is used to configure the parameters of the selected interface components based on the user requirement information. The interface generation module is used to assemble the interface components after the parameters are configured to generate an interactive interface.

9. A computer device, characterized in that, The method includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the steps of the interactive interface generation method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the interactive interface generation method as described in any one of claims 1 to 7.

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