Intelligent assistant interface automatic generation device and method and storage medium

Abstract

The invention relates to an automatic generation device for an intelligent assistant interface, and the device comprises an input analysis module which is used for receiving and understanding the demands and input of a user; the AI recommendation system uses a machine learning model to understand the requirements of the user, and selects the most suitable design elements and styles from the existing template library; designing a template library which comprises a series of predefined interface templates and elements so as to adapt to the requirements of different users and different scenes; the interface generation module is used for combining the user demand, the AI recommendation result and the design template, performing combination and rendering according to a certain logic and rule, and generating an expected interface; the previewing and editing module is used for allowing the user to perform real-time previewing and editing on the generated interface; according to the method, through the modes of enhancing the individuation function, optimizing code generation, providing the template library, using the AI technology and the like, high individuation, high universality and high expansibility are achieved, the complexity of manual operation is reduced, the design efficiency is improved, and the design cost is reduced.

Description

[Technical field]

[0001] The present invention relates to the field of big data processing technology, and specifically to an intelligent assistant interface automatic generation device, method and storage medium. [Background Technology]

[0002] At present, the main structure and principle of intelligent assistant interface generation usually include data layer, business logic layer and presentation layer. Among them, the data layer is responsible for providing the data required for the interface, the business logic layer is used to process data and execute specified commands, and the presentation layer is responsible for interface display; after the user operates on the interface, the business logic layer processes the user's request, obtains and processes the required information from the data layer, and then updates the presentation layer to complete an operation cycle; automated interface generation mainly automates this process, automatically mapping data and logic to the interface through predefined templates or rules. However, such technology has some challenges and the following shortcomings:

[0003] (1) High complexity: For complex interface designs, automated generation may not be as detailed and precise as manual design.

[0004] (2) Poor personalization: Automated tools may not be able to meet highly personalized design requirements well.

[0005] (3) Poor scalability and maintainability. The automatically generated code may be difficult to read and maintain, and it is difficult to make subsequent modifications and expansions.

[0006] (4) Performance issues: The automatically generated interface may contain redundant code or layout, which may affect the performance of the application. [Summary of the invention]

[0007] The purpose of the present invention is to solve the above-mentioned deficiencies and provide a device for automatically generating an intelligent assistant interface. By enhancing personalized functions, optimizing code generation, providing a template library and using AI technology, etc., it achieves strong personalization, versatility and extensibility, reduces the complexity of manual operations, improves design efficiency, and significantly reduces design costs.

[0008] In one aspect, the present invention provides a device for automatically generating an intelligent assistant interface, comprising:

[0009] Input parsing module, used to receive and understand user needs and input;

[0010] AI recommendation system, which uses machine learning models to understand user needs and select the most suitable design elements and styles from the existing template library;

[0011] Design template library, including a series of predefined interface templates and elements to meet the needs of different users and different scenarios;

[0012] The interface generation module is used to combine user needs, AI recommendation results and design templates, and combine and render them according to certain logic and rules to generate the expected interface.

[0013] As an embodiment, in the input parsing module, the user's needs include but are not limited to the layout of the interface, element definition, color theme, and interactive behavior. The input parsing module parses the user's input into clear design instructions and parameters.

[0014] As an embodiment, in the design template library, the interface templates and elements are static buttons and colors, or dynamic components that can respond to user interactions.

[0015] As an embodiment, the interface generation module includes a suitable layout algorithm and a rendering engine. The interface generation module combines user needs and AI recommendation results in an automated manner to generate an interface that meets the requirements.

[0016] As an embodiment, it also includes a preview and editing module, the input end of the preview and editing module is connected to the input parsing module and the AI ​​recommendation system, the preview and editing module allows the user to perform real-time preview and editing on the generated interface, and directly feedback the modification information, and feed back the feedback to the input parsing module and the AI ​​recommendation system, thereby gradually optimizing the generation device.

[0017] On the other hand, the present invention provides a method for automatically generating an intelligent assistant interface, comprising the following steps: first, the user's needs are parsed into structured data by an input module; then, the AI ​​recommendation system uses deep learning or reinforcement learning algorithms to recommend interface designs and styles that meet the needs from a design template library based on these data; thereafter, the interface generation module combines the user needs and AI recommendations in an automated manner to generate an interface that meets the requirements.

[0018] As an embodiment, the method of the present invention also includes preview and editing steps after the interface is generated. The user performs real-time preview and editing on the generated interface, and directly feeds back the modification information, and feeds back the feedback information to the input parsing module and the AI ​​recommendation system, thereby gradually optimizing the generation device.

[0019] As an embodiment, the method of the present invention comprises the following specific steps:

[0020] Demand input: Users provide design requirements through the input parsing module;

[0021] Requirements analysis: The input analysis module converts the design requirements input by the user into parameters that the system can understand, describing the interface structure and style that the user wants;

[0022] Template recommendation: The AI ​​recommendation system analyzes these parameters, matches them with the elements in the template library, finds the design elements and styles that best meet the requirements, generates and returns a recommendation list;

[0023] Selection and adjustment: Users select and adjust the designs recommended by AI. Meanwhile, these user feedback will be recorded by the system to further optimize the working effect of the AI ​​recommendation system.

[0024] Interface generation: Based on AI recommendations and user selections, the interface generation module starts building the interface and ensures that the generated interface is optimized in terms of performance and effectiveness;

[0025] Preview and edit: Users can view and edit the generated interface in real time in the preview module. They can modify any unsatisfactory parts directly and view the adjusted results in the preview module.

[0026] Feedback optimization: The modifications or feedback made by users to the automatically generated interface will be used as training samples to further improve the accuracy of the system and user satisfaction.

[0027] According to a third aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, and the program executes the above method.

[0028] In a fourth aspect of the present invention, a computer device is proposed, comprising: a processor, a memory and a bus; the processor and the memory are connected via the bus; the memory is used to store programs, the processor is used to run programs, and the above method is executed when the program is run.

[0029] Compared with the prior art, the present invention has the following advantages:

[0030] (1) Strong personalization: The present invention can better understand and meet the personalized needs of users through the AI ​​recommendation system, provide users with customized interface design, and improve user satisfaction.

[0031] (2) High efficiency: The automated interface generation process of the present invention reduces the complexity of manual operations, saves design and development time, and improves design efficiency.

[0032] (3) Real-time preview and editing: The present invention enables users to view the results of interface generation in real time in the preview module, and to modify and optimize them, thereby enhancing the user's operating experience.

[0033] (4) Continuous optimization: The present invention realizes that the modifications or feedback made by users to the automatically generated interface will be used as training samples to further improve the working effect of the AI ​​recommendation system, so that the system can continuously optimize and learn itself.

[0034] (5) Generated code optimization: The code generated by the present invention can ensure easy reading, easy maintenance, high performance, and avoid redundancy, thereby avoiding the reading and writing difficulties and performance problems that may be caused by automatically generated code.

[0035] (6) Strong versatility and expansibility: The template library of the present invention provides a wealth of design elements and styles, which can meet the design requirements of different fields and scenarios; at the same time, the system design allows the addition of new templates and elements, and has strong expansibility.

[0036] (7) Reducing design costs: The automated design process of the present invention can significantly reduce design costs, especially for large-scale and complex interface design projects, saving a lot of manpower and material costs. [Drawings]

[0037] Figure 1 It is a principle block diagram of the present invention;

[0038] Figure 2 It is a schematic diagram of the composition of the device of the present invention;

[0039] Figure 3 is a flow chart of the method of the present invention;

[0040] Figure 4 It is a structural schematic diagram of the computer device of the present invention. [Specific implementation method]

[0041] References to "one embodiment" or "some embodiments" etc. described in this specification mean that a particular feature, structure or characteristic described in conjunction with the embodiment is included in one or more embodiments of the present invention. Thus, the phrases "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. appearing in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0042] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments:

[0043] As attached Figure 2 As shown, the present invention provides a device for automatically generating an intelligent assistant interface, aiming to solve the problems in the prior art, mainly by enhancing personalized functions, optimizing code generation, providing advanced templates and using AI technology to optimize user experience and performance.

[0044] The main components of the intelligent assistant interface automatic generation device of the present invention are:

[0045] 1. Input parsing module: responsible for receiving and understanding user needs and input, which may include interface layout, element definition, color theme, interactive behavior, etc.; it needs to be able to parse user input into clear design instructions and parameters.

[0046] 2. AI recommendation system: It is the core part of the intelligent assistant. It uses machine learning models to understand user needs and select the most suitable design elements and styles from the existing template library. It can implement custom mode or automatic mode to recommend elements such as layout, color, style and other features to users.

[0047] 3. Design template library: includes a series of predefined interface templates and elements. These templates and elements must meet basic design specifications while also having a certain degree of versatility to meet the needs of different users and different scenarios. They can be static, such as simple buttons and colors, or dynamic, such as components that can respond to user interactions.

[0048] 4. Interface generation module: Combine user needs, AI recommendation results and design templates, combine and render them according to certain logic and rules to generate the expected interface; this part needs to include appropriate layout algorithms and rendering engines to ensure that the generated interface is beautiful and responsive.

[0049] 5. Preview and edit module: allows users to preview and edit in real time on the generated interface. Users can directly provide feedback on modification information. These feedbacks will reach the input parsing module and AI recommendation system to gradually optimize the effect of the generated device.

[0050] The working principle of the method for automatically generating the intelligent assistant interface of the present invention is as follows: First, the user's needs are parsed into structured data by the input module. Then, based on these data, the AI ​​recommendation system uses deep learning or reinforcement learning algorithms to recommend interface designs and styles that meet the needs from the design template library. After that, the interface generation module combines the user's needs and AI recommendations in an automated manner to generate an interface that meets the requirements. Finally, the user can preview and edit the generated interface in real time, and their feedback is used to further optimize the system performance.

[0051] In some other embodiments, as shown in the attached Figure 3 As shown, the present invention provides a method for automatically generating an intelligent assistant interface, and the specific detailed steps are as follows:

[0052] (1) Demand input: Users provide design requirements through the input parsing module, including but not limited to design elements, style, layout, color, interactive behavior, etc.

[0053] (2) Requirements analysis: The input analysis module converts the design requirements input by the user into parameters that the system can understand, describing the interface structure and style that the user wants.

[0054] (3) Template recommendation: The AI ​​recommendation system analyzes these parameters, matches them with the elements in the template library, finds the design elements and styles that best meet the requirements, and generates and returns a recommendation list.

[0055] (4) Selection and adjustment: Users can choose from the designs recommended by AI and make adjustments to them, such as changing the color, font, etc. At the same time, these user feedback will be recorded by the system to further optimize the working effect of the AI ​​recommendation system.

[0056] (5) Interface generation: Based on AI recommendations and user selections, the interface generation module begins to build the interface and ensures that the generated interface is optimized in terms of performance and effectiveness.

[0057] (6) Preview and Edit: Users can view and edit the generated interface in real time in the preview module. If they are not satisfied with the result, they can modify it directly. The adjusted result can be viewed immediately in the preview module.

[0058] (7) Feedback optimization: The modifications or feedback made by users to the automatically generated interface will be used as training samples to further improve the accuracy of the system and user satisfaction.

[0059] The present invention will be further described below in conjunction with specific embodiments:

[0060] Assume that user Tom wants to design a web interface for book management. He wants a convenient search function and a list display of book information. He also wants the interface to be simple and concise. The generation steps are as follows:

[0061] (1) Tom uses the input parsing module to describe the interface elements he wants: a search bar, a book list, and the interface style he requires: concise and simple.

[0062] (2) The input parsing module interprets Tom’s needs and converts these unstructured requirements into quantifiable parameters, namely: the elements include a search bar and a book list, and the style is simple and plain.

[0063] (3) These parameters are fed into the AI ​​recommendation system. Based on these parameters, the AI ​​system recommends several sets of interface designs with simple styles, including search bars and book lists, from a rich library of design templates, and presents these recommendations to Tom.

[0064] (4) Tom selected his favorite design from the ones recommended by AI and made some adjustments to some details, such as the column width and font size of the list.

[0065] (5) Based on Tom’s selections and requirements, the interface generation module begins to build the interface; it will automatically combine user requirements and AI recommendation results to generate an interface that meets Tom’s imagination.

[0066] (6) The generated interface will be presented in the preview module. Tom can view the appearance of his interface in the preview module and edit the interface in real time, such as adjusting the color, position, etc.

[0067] (7) During use, Tom made some other suggestions and requirements for the interface, which will be used as feedback to further optimize the AI ​​recommendation accuracy and system performance.

[0068] In this way, a library management interface that meets the user's expectations is generated through the new intelligent assistant interface automatic generation device, and Tom only needs to describe and select without worrying too much about the complexity of technical implementation and coding.

[0069] In some other embodiments, the Figure 4 The figure is a schematic diagram of a computer device of the present invention. The computer device includes a processor, a memory and a bus; the processor and the memory are connected via a bus, the memory is used to store programs, and the processor is used to run programs, and when the programs are run, the method for automatically generating an intelligent assistant interface provided by the present invention is executed. Furthermore, the present invention also provides a computer-readable storage medium, the computer-readable storage medium includes a stored program, and the program executes the method for automatically generating an intelligent assistant interface provided by the present invention.

[0070] The computer device may be a desktop computer, a notebook computer, a PDA, a cloud server, or other computing device. Figure 4 It is only an example of a computer device and does not constitute a limitation of the computer device. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0071] The processor may be a central processing unit CPU, or other general-purpose processors, digital signal processors DSP, application-specific integrated circuits ASIC, off-the-shelf programmable gate arrays FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the computer device, and uses various interfaces and lines to connect various parts of the entire computer device.

[0072] The memory can be used to store computer programs and / or modules / units. The processor realizes various functions of the computer device by running or executing the computer programs and / or modules / units stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the computer device (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card SMC, a secure digital SD card, a flash memory card, at least one disk storage device, a flash memory device or other volatile solid-state storage device.

[0073] If the functions described in the method of the embodiment of the present invention are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the part of the embodiment of the present invention that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, mobile computing device or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention; and the aforementioned storage medium includes various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories, random access memories, disks or optical disks. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0074] The above embodiments are only used to illustrate the technical solutions of the present invention, but not to limit it. Under the idea of ​​the present invention, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other changes in different aspects of the present invention as described above. Although the present invention is described in detail with reference to the above embodiments, it should be understood by those skilled in the art that the technical solutions described in the above embodiments can still be modified, or some of the technical features can be replaced by equivalents. However, these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

[0075] The present invention is not limited to the above-mentioned implementation modes, and any other changes, modifications, substitutions, combinations, and simplifications made without departing from the spirit and principle of the present invention shall be equivalent replacement modes and shall be included in the protection scope of the present invention.

Claims

1. A device for automatically generating an intelligent assistant interface, characterized in that: include: Input parsing module, used to receive and understand user needs and input; AI recommendation system, which uses machine learning models to understand user needs and select the most suitable design elements and styles from the existing template library; Design template library, including a series of predefined interface templates and elements to meet the needs of different users and different scenarios; The interface generation module is used to combine user needs, AI recommendation results and design templates, and combine and render them according to certain logic and rules to generate the expected interface.

2. The device according to claim 1, characterized in that: In the input parsing module, the user's needs include but are not limited to the layout of the interface, element definition, color theme, and interactive behavior. The input parsing module parses the user's input into clear design instructions and parameters.

3. The device according to claim 1, characterized in that: In the design template library, the interface templates and elements are static buttons and colors, or dynamic components that can respond to user interactions.

4. The device according to claim 1, characterized in that: The interface generation module includes a suitable layout algorithm and a rendering engine. The interface generation module combines user needs and AI recommendation results in an automated manner to generate an interface that meets the requirements.

5. The device according to claim 1, characterized in that: It also includes a preview and editing module, the input end of which is connected to the input parsing module and the AI ​​recommendation system. The preview and editing module allows the user to perform real-time preview and editing on the generated interface, and directly feedback the modification information, and feed back the feedback to the input parsing module and the AI ​​recommendation system, thereby gradually optimizing the generation device.

6. A method for automatically generating an intelligent assistant interface, characterized in that: The following steps are included: first, the user's needs are parsed into structured data by the input module; Then, based on this data, the AI ​​recommendation system uses deep learning or reinforcement learning algorithms to recommend interface designs and styles that meet the requirements from the design template library; after that, the interface generation module combines user needs and AI recommendations in an automated manner to generate an interface that meets the requirements.

7. The method according to claim 6, characterized in that: After the interface is generated, it also includes preview and editing steps. Users perform real-time preview and editing on the generated interface, directly feedback the modification information, and then feed back the feedback information to the input parsing module and AI recommendation system, thereby gradually optimizing the generation device.

8. The method according to claim 6, characterized in that The following steps are involved: Demand input: Users provide design requirements through the input parsing module; Requirements analysis: The input analysis module converts the design requirements input by the user into parameters that the system can understand, describing the interface structure and style that the user wants; Template recommendation: The AI ​​recommendation system analyzes these parameters, matches them with the elements in the template library, finds the design elements and styles that best meet the requirements, generates and returns a recommendation list; Selection and adjustment: Users select and adjust the designs recommended by AI. Meanwhile, these user feedback will be recorded by the system to further optimize the working effect of the AI ​​recommendation system. Interface generation: Based on AI recommendations and user selections, the interface generation module starts building the interface and ensures that the generated interface is optimized in terms of performance and effectiveness; Preview and edit: Users can view and edit the generated interface in real time in the preview module. They can modify any unsatisfactory parts directly and view the adjusted results in the preview module. Feedback optimization: The modifications or feedback made by users to the automatically generated interface will be used as training samples to further improve the accuracy of the system and user satisfaction.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program that executes the method of claim 6 , 7 or 8 .

10. A computer device, characterized in that: include: processor, memory, and bus; The processor is connected to the memory via the bus; The memory is used to store a program, and the processor is used to run the program. When the program is run, the method according to claim 6, 7 or 8 is executed.

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