A front-end interface generation method based on data standards

Abstract

A method for generating a front-end interface based on data standards comprises the following steps: extracting metadata of a data standard specification document through document preprocessing, named entity recognition, and relationship extraction; the metadata comprises: field names, data types, constraints, table names, and field descriptions in the data standard specification document; combing and defining the extracted metadata, including: defining field names, grouping types, value types, whether required, security levels, English names, length ranges, field permissions, and default values; dynamically generating front-end layouts and interactive functions according to metadata, and generating a front-end interface; when data changes, updating the front-end interface through a publish-subscribe method. The method of the present invention extracts metadata from a data standard specification document, dynamically generates a front-end interface based on the metadata of the data standard; supports dynamic rendering, and when data changes, the front-end interface can be updated in real time, thereby improving the flexibility and response speed of the application.

Description

Technical Field

[0001] The present invention relates to the technical field of front-end interface generation, and in particular to a front-end interface generation method based on data standards. Background Art

[0002] With the continuous advancement of front-end software development technology and the acceleration of digital transformation, data has become a core element of enterprise decision-making, business promotion and management optimization. In order to ensure the accuracy and security of data and improve the efficiency of data collection, integration and utilization, various industries have established data standard systems. Under the requirements of the standard system, the traditional software development model relies on manual coding and a lot of repetitive work, which not only increases development costs, but also limits the consistency and maintainability of the interface.

[0003] Data standards are often announced in normative documents issued by the state, province, and city. Each industry develops corresponding systems to collect corresponding data according to the announced data standards, forming a data platform and database with industry characteristics. At present, there are two general ways of information processing. The first way is to customize and develop corresponding business systems according to various data standards. This method has high R&D costs and is inconvenient to maintain. The second way is to complete the development of business data forms through defined form controls and configurations, without writing a lot of code to achieve business data collection. This method cannot meet complex or specific data. This requires a more intelligent way that can parse the metadata in the data standard, extract the elements, layout, interaction logic and other information required for the interface, and use technologies such as front-end frameworks and form engines to convert this information into executable code and generate the corresponding front-end interface.

[0004] At present, there is no comprehensive automated solution for extracting metadata from published data standard specification documents and automatically generating front-end interactive pages based on metadata. To implement a front-end interface generation method based on data standards, it is necessary to involve metadata extraction, management, front-end development frameworks, and automation tools. It faces challenges such as complexity, diversity, and diversity of front-end requirements. The specific difficulties are as follows:

[0005] 1. Data standard specifications can be very complex, containing a large amount of metadata and complex logical relationships, which makes it difficult to extract and parse metadata;

[0006] 2. Different data standards may use different formats and conventions, which requires the solution to be highly flexible and scalable;

[0007] 3. The requirements for front-end interactive pages may vary depending on the user, device, and context, which increases the complexity of automatically generating front-end pages. Summary of the invention

[0008] In order to solve the defects of the prior art, the purpose of the present invention is to provide a front-end interface generation method based on data standards, support automatic generation and dynamic rendering of front-end interfaces based on data standard specification documents, improve the clarity of data description, promote the dataization of various industry standards and improve the informatization level of various industries.

[0009] In order to achieve the above object, the present invention provides a method for generating a front-end interface based on data standards, comprising the following steps:

[0010] Extract metadata of the data standard specification document through document preprocessing, named entity recognition, and relationship extraction; the metadata includes: field names, data types, constraints, table names, and field descriptions in the data standard specification document;

[0011] Sort out and define the extracted metadata, including: define field name, group type, value type, whether it is required, security level, English name, length range, field permissions, and default value;

[0012] Dynamically generate front-end layout and interactive functions based on metadata to generate front-end interface;

[0013] When the data changes, the front-end interface is updated through the publish-subscribe method.

[0014] Furthermore, the document preprocessing is to process the data standard specification document through text cleaning, format standardization and structured parsing; wherein format standardization includes unifying the case of field names, removing unnecessary spaces and punctuation marks.

[0015] Furthermore, the named entity recognition includes:

[0016] By training a named entity recognition model, the named entities in the data standard specification document are identified; the named entities include: the field name, the data type, the constraint condition, the table name and the field description; or / and

[0017] Through large language models, context understanding capabilities and pattern matching, named entities can be accurately identified from data standard specification document structure and context information.

[0018] Furthermore, it also includes: in the named entity recognition stage, adjusting the named entity recognition model through a pre-trained language representation model.

[0019] Furthermore, the relationship extraction is to extract the association between field names and data types, constraints, table names and field descriptions by analyzing the document structure and content, and finally generate structured metadata by integrating and verifying the extracted named entities and associations.

[0020] Furthermore, it also includes: defining rules to identify the mapping relationship between field names and data types or determining the relationship between field names and data types, constraints, table names and field descriptions through template matching.

[0021] Furthermore, the step of dynamically generating the front-end layout and interactive functions according to the metadata further includes:

[0022] Read metadata from backend APIs or configuration files;

[0023] Create a page layout structure based on the group name and organize the fields into groups;

[0024] Traverse the field metadata and dynamically render the corresponding input control according to the value type;

[0025] Apply corresponding styles or tags based on the information in the metadata;

[0026] For fields with length restrictions, set corresponding input restrictions;

[0027] Add validation logic to form fields based on whether they are required and the value type information;

[0028] Generate permission control logic on the front end to hide or disable input of certain fields based on field permissions;

[0029] On page load, set default values ​​for fields that have default values;

[0030] Provide real-time prompts and feedback based on user input and verification results.

[0031] Furthermore, when the data changes, the step of updating the front-end interface by publishing and subscribing further includes:

[0032] Define publishers and subscribers. The publisher is used to publish an event or message containing new data when data changes; the subscriber is used to subscribe to data change events from the publisher.

[0033] The subscriber registers with the publisher by calling the publisher's subscription function or method and passing in a callback function as the subscription processing logic;

[0034] When the data changes, the publisher triggers an event and sends the new data as a part of the data change event or additional information to all subscribers who subscribe to the data change event;

[0035] The subscriber receives the data change event, executes the callback function, and updates the state or interface according to the received new data.

[0036] To achieve the above-mentioned purpose, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is used to execute the computer program stored in the memory to implement the front-end interface generation method based on data standards as described above.

[0037] To achieve the above objectives, the present invention also provides a computer-readable storage medium, in which a computer program is stored. The computer program is loaded and executed by a processor to implement the front-end interface generation method based on data standards as described above.

[0038] The front-end interface generation method based on data standards provided by the present invention has the following beneficial effects compared with the prior art:

[0039] Metadata is extracted from data standard specification documents, and content, layout and interactive functions are dynamically generated based on the metadata of the data standards, which greatly reduces the workload of manually writing front-end code and improves the efficiency of data business system development; the present invention supports dynamic rendering, and when the data changes, the front-end interface can be updated in real time, which improves the flexibility and response speed of the application.

[0040] Other features and advantages of the present invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0042] Figure 1 A flow chart of a method for generating a front-end interface based on data standards according to an embodiment of the present invention;

[0043] Figure 2 FIG. 1 is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0045] Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present invention. It should be understood that the drawings and embodiments of the present invention are only for exemplary purposes and are not intended to limit the scope of protection of the present invention.

[0046] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0047] It should be noted that the modifications of "one" and "plurality" mentioned in the present invention are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more". "Plurality" should be understood as two or more.

[0048] In an embodiment of the present invention, a method for generating a front-end interface based on data standards is provided, the method comprising: extracting metadata from a data standard specification document; combing and defining the metadata; dynamically generating a front-end layout and interactive functions according to the metadata to generate a front-end interface; and updating the front-end interface by publishing and subscribing when the data changes.

[0049] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0050] Figure 1 Flow chart of a method for generating a front-end interface based on data standards according to an embodiment of the present invention. Figure 1 The specific implementation of the front-end interface generation method based on data standards of the present invention is as follows.

[0051] In step 101, metadata in a data standard specification document is extracted.

[0052] In the embodiments of the present invention, by integrating a large language model (such as Tide GPT) and advanced natural language processing technology, combined with document preprocessing, named entity recognition (NER), relationship extraction and other technical means, metadata in data standard specification documents is automatically extracted, and the automatic extraction and structuring of metadata is innovatively realized.

[0053] The metadata includes the field name, data type, constraint conditions, table name and field description in the data standard specification document, and is characterized by structure, consistency and professionalism.

[0054] During the document preprocessing stage, the consistency and accuracy of data standard specification document data are ensured through text cleaning, format standardization and structured parsing.

[0055] In an embodiment of the present invention, text cleaning is performed on a data standard specification document to remove irrelevant information (such as comments, footnotes, copyright notices, etc.) from the content of the data standard specification document, remove redundant spaces, line breaks, tabs, and non-printing characters, and remove stop words that are irrelevant to information extraction.

[0056] In the embodiment of the present application, the structured analysis of the data standard specification document is to convert the unstructured text data into a structured data format, including word segmentation and syntactic analysis, dividing the text into words, analyzing the sentence structure to identify the subject, predicate, and object, etc.; identifying the key field names, data types, constraints, etc. in the document; identifying the relationship and constraints between fields, such as primary keys, foreign keys, unique constraints, etc. The final result is generated in a structured Json format.

[0057] In the embodiment of the present invention, in the document preprocessing stage, format standardization is mainly applied to the original data standard specification document, including unifying the case of field names, removing extra spaces and punctuation marks, etc., to ensure that the information is clearly expressed and easy to process. The generated metadata may require further format standardization in the subsequent processing process to meet the requirements of specific applications or systems. For example, before importing metadata into a database or other data storage system, the field names and data types need to be further sorted and defined according to the naming conventions and data type specifications of the target system.

[0058] In the embodiments of the present invention, domain-specific named entity recognition (NER, also known as "proper name recognition", which refers to identifying entities with specific meanings in text) technology is adopted to train a domain-specific NER model to identify key named entities in documents, including field names, data types, constraints, table names, and field descriptions. And through the large language model (GPT model), the context understanding ability and pattern matching are used to accurately identify these named entities from the data standard specification document structure and context information.

[0059] In an embodiment of the present invention, in the named entity recognition (NER) stage, adjustments can be made through pre-trained language representation models (such as BERT, RoBERTa, etc.) to improve the recognition accuracy of the named entity recognition model in specific fields (such as database fields, constraints), so as to better understand and identify named entities in data standard specification documents, and improve the quality and accuracy of metadata extraction. BERT stands for Bidirectional Encoder Representation from Transformers, which is a pre-trained language representation model. It emphasizes that it no longer uses the traditional unidirectional language model or the shallow splicing method of two unidirectional language models for pre-training as in the past, but uses a new masked language model (MLM, masked language model) to generate deep bidirectional language representation. The RoBERTa model is an improved version of BERT. In terms of model scale, computing power and data, RoBERTa has a larger model parameter amount, batch size, and more training data.

[0060] In an embodiment of the present invention, in the relationship extraction stage, by analyzing the document structure and content, the relationship between the field name and the data type, constraints, table name and field description is extracted. Finally, high-quality structured metadata is generated by integrating and verifying the extracted named entities and relationships. The generated metadata provides a solid data foundation for the generation of automated front-end interfaces, significantly improves the efficiency and accuracy of data processing, realizes seamless connection from data standard specification documents to data applications, and promotes the innovative development of data standardization and intelligent management.

[0061] Furthermore, customized rules and templates can be used to extract the relationships between named entities. For example, rules can be defined to identify the mapping relationship between field names and data types or to determine the relationship between field names and constraints through template matching, which helps to effectively extract key information according to data standard specification document structure and grammatical characteristics.

[0062] In step 102, the extracted metadata is sorted and defined.

[0063] First, in step 1021, the metadata finally extracted in step 101 is defined, including:

[0064] Field name: the field name used for display and identification on the page;

[0065] Group Name: Group fields into logical groups for easier organization in the layout;

[0066] Value type: determines the input type of the field (such as text, number, date, etc.);

[0067] Required: Indicates whether the field must be filled in when submitting;

[0068] Security level: may be used to determine the encryption level or access control of the field;

[0069] English Name: The English name of the field, which may be used in API requests or database field names;

[0070] Length Range: Defines the maximum and minimum length of the field value (if applicable);

[0071] Field permissions: define which users or roles can access or modify the field;

[0072] Default value: The value used when the field is not filled in.

[0073] Application Program Interface (API) is a set of definitions, programs and protocols that enable computer software to communicate with each other through API interfaces. One of the main functions of API is to provide a common set of functions. Programmers can reduce programming tasks by developing applications by calling API functions. API is also a kind of middleware that provides data sharing for various platforms.

[0074] In step 103, the front-end layout and interactive functions are dynamically generated according to the metadata to generate a front-end interface.

[0075] Dynamically generate front-end layout, including:

[0076] Read metadata: read metadata from the backend API or configuration file;

[0077] Create layout structure: Create the layout structure of the page according to the group name and organize the fields into groups;

[0078] Dynamically render fields: traverse the field metadata and dynamically render the corresponding input controls (such as text boxes, number boxes, date pickers, etc.) according to the value type.

[0079] Apply styles: Apply different styles or tags based on other information in the metadata. For example, in the security level setting, metadata may contain security-related data, such as the sensitivity of the data, access rights, etc. When interface elements (such as buttons, text boxes, menu items, etc.) need to reflect the security level of the data, red can be used to indicate a high security level (special permissions are required to access), green can be used to indicate a low security level (most users can access), a lock icon can be used to indicate that the element requires encrypted access, and a text prompt can be added below or next to the control to briefly explain its security level and access requirements;

[0080] Handle length restrictions: For fields with length restrictions, set corresponding input restrictions.

[0081] Dynamically generate interactive features, including:

[0082] Perform form validation: Add validation logic to form fields based on whether they are required and the value type. For example, required fields cannot be left blank when submitted, and numeric fields can only accept numeric input;

[0083] Permission control: Implement basic permission control logic on the front end, hide or disable input of certain fields based on field permissions, and stricter permission control should be implemented on the back end;

[0084] Default value handling: When the page loads, set default values ​​for fields that have default values;

[0085] Dynamic prompts and feedback: Provide instant prompts and feedback based on user input and verification results.

[0086] In step 104, when the data changes, the front-end interface can be updated through the Publish-Subscribe method. This method allows decoupling between components and improves the flexibility and maintainability of the application. The following is a detailed description of updating the front-end interface when the data changes through the Publish-Subscribe method:

[0087] Define publishers and subscribers:

[0088] Publisher: is the component or module responsible for sending data change messages. When data changes, the publisher will publish an event or message containing the new data.

[0089] Subscriber: A component or module that is interested in specific data changes and wants to be notified when they occur. Subscribers subscribe to data change events that interest them from publishers.

[0090] Subscription process:

[0091] Subscribers register themselves with publishers to express their interest in one or more data change events. This is usually done by calling the publisher's subscription function or method and passing in a callback function as the subscription processing logic.

[0092] Data changes and releases:

[0093] When the data changes, the publisher triggers an event and sends the new data as part of the event or as additional information. This event will be received by all subscribers who have subscribed to the event.

[0094] Update the front-end interface:

[0095] After receiving the data change event, the subscriber will execute the previously registered callback function. In this callback function, the subscriber can update its status or interface according to the new data received.

[0096] In the embodiment of the present invention, the publish-subscribe method is used to update the interface, which has the following advantages:

[0097] Decoupling and flexibility: Through the publish-subscribe method, the publisher and subscriber of data changes are loosely coupled. The publisher does not need to know which subscribers exist, but only needs to publish events; and the subscriber does not need to know which publisher publishes the event, but only needs to process the event that he is interested in. This decoupling makes the application more flexible, easy to maintain and expand.

[0098] Wide application scenarios:

[0099] The publish-subscribe method is applicable to a variety of scenarios, such as page status update, data processing completion notification, asynchronous operation completion callback, etc. In these scenarios, when an event occurs (such as data change), related components or modules can automatically update their own status or interface by subscribing to the event.

[0100] The present invention uses advanced natural language processing technologies such as format standardization, word segmentation and syntactic parsing, named entity recognition (NER), relationship extraction and context understanding, combined with pre-trained model fine-tuning, customized rules and templates, automatic correction and manual review, to comprehensively improve the clarity of data description and ensure the accuracy, consistency and readability of metadata.

[0101] During the integration and verification phase, an automatic correction mechanism is introduced to detect and fix possible data errors or inconsistencies, such as detecting duplicate field names or incomplete constraints, and automatically correcting them or reminding users to perform manual processing to ensure that the generated metadata is accurate.

[0102] The present invention extracts metadata from data standard specification documents through a parser (including document preprocessing, named entity recognition, and relationship extraction functions), and dynamically generates content, layout, and interactive functions based on metadata, greatly reducing the workload of manually writing front-end code and improving development efficiency. The invention supports dynamic rendering. When the data changes, the front-end interface can be updated in real time, improving the flexibility and response speed of the application. This enables the standards and specifications of various industries to be presented to users in a standardized and visual manner, improving the readability and ease of use of the standards, and helping to promote technological progress in data management, interface development, and other aspects of the construction industry, and improving the information level of the entire industry.

[0103] The present invention provides a metadata extraction method based on data standard specification documents issued by the state, province and city, as well as a decomposition method for parsing metadata and automatically generating a front-end interactive interface, which greatly reduces the research and development costs of customized development of data business systems and drag-and-drop semi-automatic development, and promotes various industries to continuously optimize the accuracy of data collection, the depth of analysis and the effectiveness of data application based on data standards.

[0104] In an embodiment of the present invention, an electronic device is also provided. Figure 2 Schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Figure 2 As shown, the electronic device of the present invention includes a processor 201 and a memory 202, wherein:

[0105] The memory 202 stores a computer program. When the computer program is read and executed by the processor 201, the computer program executes the steps in the embodiment of the method for generating a front-end interface based on data standards as described above.

[0106] In an embodiment of the present invention, a computer-readable storage medium is further provided, in which a computer program is stored, wherein the computer program is configured to execute the steps in the embodiment of the front-end interface generation method based on data standards when running.

[0107] In this embodiment, the above-mentioned computer-readable storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

[0108] Those skilled in the art can understand that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention is described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions recorded in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A front-end interface generation method based on data standards, characterized in that: The following steps are involved: Extract metadata of the data standard specification document through document preprocessing, named entity recognition, and relationship extraction; the metadata includes: field names, data types, constraints, table names, and field descriptions in the data standard specification document; Sort out and define the extracted metadata, including: define field name, group type, value type, whether it is required, security level, English name, length range, field permissions, and default value; Dynamically generate front-end layout and interactive functions based on metadata to generate front-end interface; When the data changes, the front-end interface is updated through publishing and subscription; The named entity recognition comprises: By training a named entity recognition model, the named entities in the data standard specification document are identified; the named entities include: the field name, the data type, the constraint condition, the table name and the field description; and Through large language models, context understanding capabilities and pattern matching, named entities can be accurately identified from data standard specification document structures and context information; The relationship extraction is to extract the association between field names and data types, constraints, table names and field descriptions by analyzing the document structure and content, and finally generate structured metadata by integrating and verifying the extracted named entities and associations; The step of dynamically generating the front-end layout and interactive functions according to the metadata further includes: Read metadata from backend APIs or configuration files; Create a page layout structure based on the group name and organize the fields into groups; Traverse the field metadata and dynamically render the corresponding input control according to the value type; Apply corresponding styles or tags based on the information in the metadata; For fields with length restrictions, set corresponding input restrictions; Add validation logic to form fields based on whether they are required and the value type information; Generate permission control logic on the front end to hide or disable input of certain fields based on field permissions; On page load, set default values ​​for fields that have default values; Provide real-time prompts and feedback based on user input and verification results; The named entity recognition further includes: defining rules to identify the mapping relationship between field names and data types or determining the relationship between field names and data types, constraints, table names, and field descriptions through template matching; Before importing the metadata into a database or data storage system, the field names and the data types need to be sorted out and defined again according to the naming convention and data type specification of the target system to meet the requirements of the target system.

2. The method for generating a front-end interface based on data standards according to claim 1, characterized in that: The document preprocessing is to process the data standard specification document through text cleaning, format standardization and structured parsing; wherein format standardization includes unifying the case of field names and removing unnecessary spaces and punctuation marks.

3. The method for generating a front-end interface based on data standards according to claim 1, characterized in that: Also includes: In the named entity recognition stage, the named entity recognition model is adjusted through a pre-trained language representation model.

4. The method for generating a front-end interface based on data standards according to claim 1, characterized in that: The step of updating the front-end interface by publishing and subscribing when the data changes further includes: Define publishers and subscribers. The publisher is used to publish an event or message containing new data when data changes; the subscriber is used to subscribe to data change events from the publisher. The subscriber registers with the publisher by calling the publisher's subscription function or method and passing in a callback function as the subscription processing logic; When the data changes, the publisher triggers an event and sends the new data as a part of the data change event or additional information to all subscribers who subscribe to the data change event; The subscriber receives the data change event, executes the callback function, and updates the state or interface according to the received new data.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: The processor is used to execute the computer program stored in the memory to implement the steps of the front-end interface generation method based on data standards as described in any one of claims 1-4.

6. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, which is loaded and executed by a processor to implement the steps of the method for generating a front-end interface based on data standards as described in any one of claims 1 to 4.

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