Intelligent document inspection system, method and equipment and storage medium

Abstract

The invention discloses an intelligent document checking system, method and device and a storage medium, the system comprises a front-end interaction module constructed based on a Vue2 framework, a back-end processing module constructed based on a SpringBoot framework, and the front-end interaction module is used for receiving a to-be-checked document and a corresponding document format requirement; the back-end processing module performs format analysis and wrongly written character recognition on a to-be-checked document through a format checking unit, a basic wrongly written character recognition unit and an AI enhancement checking unit according to a preset checking rule on the basis of a document format requirement so as to obtain a format checking result, a basic wrongly written character recognition result and a semantic wrongly written character recognition result; and classifying and aggregating the format check result, the basic wrongly written character recognition result and the semantic wrongly written character recognition result, generating document modification prompt information, and sending the document modification prompt information to a front-end interaction module for display. According to the method, the efficiency and accuracy of document inspection are improved by combining rule matching and AI semantic analysis technologies.

Description

Technical Field

[0001] This invention relates to the field of document processing technology, and in particular to a document intelligent inspection system, method, device, and storage medium. Background Technology

[0002] In document processing, it is often necessary to check the document's format to ensure it meets specified requirements, and to identify and correct typos. Existing document checking methods rely on manual proofreading, which is either inaccurate in format checking or inefficient in typo identification. Furthermore, most methods fail to effectively combine format checking and typo identification, resulting in low efficiency and a high risk of errors. Meanwhile, existing automated checking tools suffer from limitations in functionality, scalability, and the inability to handle complex semantic errors. This is particularly problematic when handling confidential documents, where data security and privacy protection become significant challenges. These methods fail to meet the efficiency and accuracy requirements of document processing in practical applications. Therefore, improving the efficiency and accuracy of document processing is an urgent issue that needs to be addressed.

[0003] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention The main objective of this invention is to provide a document intelligent inspection system, method, device, and storage medium, aiming to address the technical problem of how to improve the efficiency and accuracy of document processing.

[0004] To achieve the above objectives, this invention provides a document intelligent inspection system. The system includes a front-end interaction module and a back-end processing module. The front-end interaction module is built on the Vue2 framework, and the back-end processing module is built on the Spring Boot framework. The back-end processing module includes a format checking unit, a basic misspelling recognition unit, and an AI-enhanced inspection unit. The front-end interaction module is used to receive the document to be checked and the corresponding document format requirements input by the user, and send the document to be checked and the document format requirements to the back-end processing module. The backend processing module is used to perform format analysis, basic misspelling recognition, and semantic misspelling recognition on the document to be checked according to the document format requirements and preset checking rules through the format checking unit, the basic misspelling recognition unit, and the AI-enhanced checking unit, so as to obtain format checking results, basic misspelling recognition results, and semantic misspelling recognition results; The backend processing module is also used to classify and aggregate the format check results, the basic misspelling recognition results and the semantic misspelling recognition results, generate document modification prompt information, and send the document modification prompt information to the frontend interaction module for display.

[0005] Optionally, the preset inspection rule is a parallel inspection rule; Based on the document format requirements and according to preset inspection rules, the document to be inspected is analyzed for format, basic misspellings, and semantic misspellings using the format inspection unit, the basic misspelling recognition unit, and the AI-enhanced inspection unit to obtain format inspection results, basic misspelling recognition results, and semantic misspelling recognition results, including: Based on the document format requirements and in accordance with the parallel inspection rules, the document to be inspected is subjected to format analysis, basic misspelling recognition, and semantic misspelling recognition by the format inspection unit, the basic misspelling recognition unit, and the AI-enhanced inspection unit, respectively, to obtain format inspection results, basic misspelling recognition results, and semantic misspelling recognition results.

[0006] Optionally, the preset inspection rule is a sequential inspection rule; Based on the document format requirements and according to preset inspection rules, the document to be inspected is analyzed for format, basic misspellings, and semantic misspellings using the format inspection unit, the basic misspelling recognition unit, and the AI-enhanced inspection unit to obtain format inspection results, basic misspelling recognition results, and semantic misspelling recognition results, including: Based on the document format requirements, the format checking unit performs format analysis on the document to be checked. After the format analysis is completed, the format check results are obtained, and the basic misspelling recognition unit is used to identify basic misspellings in the document to be checked. After the basic misspelling recognition is completed, the basic misspelling recognition result is obtained, and the AI-enhanced inspection unit performs semantic misspelling recognition on the document to be inspected to obtain the semantic misspelling recognition result.

[0007] Optionally, the step of performing format analysis on the document to be checked by the format checking unit includes: Determine the document type of the document to be inspected; The document to be inspected is parsed using the parser corresponding to the document type to obtain the overall structure and detailed format of the document to be inspected. Determine the target format rules in the format database based on the document format requirements; The overall structure and the detailed format are analyzed based on the target format rules.

[0008] Optionally, the step of performing basic misspelling recognition on the document to be checked using the basic misspelling recognition unit includes: The document to be inspected is divided into task blocks using a document chapter division strategy; Based on the multi-threaded scanning method, the basic misspellings of the divided task blocks are identified by the basic misspelling recognition unit, which uses multiple general misspellings and multiple professional misspellings in the misspelling library.

[0009] Optionally, the AI-enhanced inspection unit includes a text cleaning subunit and a semantic analysis subunit, wherein the semantic analysis subunit is built based on the DeepSeek-R1 offline model; The AI-enhanced inspection unit performs semantic misspelling recognition on the document to be inspected, including: The text content of the document to be inspected is extracted through the text cleaning subunit; The semantic analysis subunit is used to identify semantic misspellings in the text content.

[0010] Optionally, the backend processing module further includes a result fusion unit; The format check results, the basic misspelling recognition results, and the semantic misspelling recognition results are categorized and aggregated, including: Determine the confidence level corresponding to the semantic misspelling recognition result; When the confidence level is greater than a preset threshold, the basic misspelling recognition result and the semantic misspelling recognition result are integrated and processed. The integrated typo recognition results and the format check results are categorized and aggregated.

[0011] Furthermore, to achieve the above objectives, the present invention also proposes a document intelligent inspection method, which includes the following steps: The front-end interaction module receives the document to be checked and the corresponding document format requirements input by the user, and sends the document to be checked and the document format requirements to the back-end processing module; The backend processing module performs format analysis, basic misspelling recognition, and semantic misspelling recognition on the document to be checked according to the document format requirements and preset inspection rules through the format inspection unit, the basic misspelling recognition unit, and the AI-enhanced inspection unit, so as to obtain format inspection results, basic misspelling recognition results, and semantic misspelling recognition results; The backend processing module classifies and aggregates the format check results, the basic misspelling recognition results, and the semantic misspelling recognition results, generates document modification prompts, and sends the document modification prompts to the frontend interaction module for display.

[0012] Furthermore, to achieve the above objectives, the present invention also proposes a document intelligent inspection device, the device comprising: a memory, a processor, and a document intelligent inspection program stored in the memory and executable on the processor, the document intelligent inspection program being configured to implement the steps of the document intelligent inspection method as described above.

[0013] Furthermore, to achieve the above objectives, the present invention also proposes a storage medium storing a document intelligent inspection program, which, when executed by a processor, implements the steps of the document intelligent inspection method as described above.

[0014] This invention relates to an intelligent document inspection system, comprising a front-end interaction module and a back-end processing module. The front-end interaction module is built on the Vue2 framework, and the back-end processing module is built on the Spring Boot framework. The back-end processing module includes a format inspection unit, a basic misspelling recognition unit, and an AI-enhanced inspection unit. First, the front-end interaction module receives the document to be inspected and the corresponding document format requirements input by the user, and sends the document to be inspected and the document format requirements to the back-end processing module. Then, based on the document format requirements and according to preset inspection rules, the back-end processing module performs format analysis, basic misspelling recognition, and semantic misspelling recognition on the document to be inspected through the format inspection unit, the basic misspelling recognition unit, and the AI-enhanced inspection unit to obtain format inspection results, basic misspelling recognition results, and semantic misspelling recognition results. Afterward, the back-end processing module further classifies and aggregates the format inspection results, the basic misspelling recognition results, and the semantic misspelling recognition results, generates document modification prompts, and sends the document modification prompts to the front-end interaction module for display. Compared to existing technologies that rely on manual inspection, which is inefficient and prone to errors, this invention improves the efficiency and accuracy of document inspection by combining rule matching and AI semantic analysis technologies. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the structure of a document intelligent inspection device in the hardware operating environment involved in the embodiments of the present invention; Figure 2 This is a structural block diagram of the first embodiment of the document intelligent inspection system of the present invention; Figure 3 This is a flowchart illustrating the module interaction of the first embodiment of the document intelligent inspection system of the present invention. Figure 4 This is a flowchart illustrating the first embodiment of the document intelligent inspection method of the present invention.

[0016] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0017] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0018] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of a document intelligent inspection device in the hardware operating environment involved in the embodiments of the present invention.

[0019] like Figure 1 As shown, the document intelligent inspection device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be high-speed random access memory (RAM) or stable non-volatile memory (NVM), such as a disk storage device. Optionally, the memory 1005 may also be a storage system independent of the aforementioned processor 1001.

[0020] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the document intelligent inspection device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0021] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and a document intelligent inspection program.

[0022] exist Figure 1 In the document intelligent inspection device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the document intelligent inspection device of the present invention can be set in the document intelligent inspection device, and the document intelligent inspection device calls the document intelligent inspection program stored in the memory 1005 through the processor 1001 and executes the document intelligent inspection method provided in the embodiment of the present invention.

[0023] This invention provides a document intelligent inspection system, referring to... Figure 2 and Figure 3 , Figure 2 This is a structural block diagram of the first embodiment of the document intelligent inspection system of the present invention. Figure 3 This is a communication middleware architecture diagram of the first embodiment of the document intelligent inspection system of the present invention.

[0024] In this embodiment, the document intelligent inspection system includes a front-end interaction module 2001 and a back-end processing module 2002. The front-end interaction module 2001 is built based on the Vue2 framework, and the back-end processing module 2002 is built based on the Spring Boot framework. The back-end processing module 2002 includes a format inspection unit 2021, a basic misspelling recognition unit 2022, and an AI-enhanced inspection unit 2023. This invention achieves efficient document formatting and typo checking by combining a front-end interaction module, a back-end processing module, and a database module. The front-end, based on the Vue2 framework, provides a user-friendly interface, facilitating users to input document formatting requirements and view check results; the back-end, based on the Spring Boot framework, improves system stability and scalability.

[0025] The front-end interaction module 2001 is used to receive the document to be checked and the corresponding document format requirements input by the user, and send the document to be checked and the document format requirements to the back-end processing module 2002.

[0026] It should also be noted that the front-end interaction module is developed based on the Vue2 framework, providing a simple and easy-to-use user interface. It includes a document inspection rule selection button, a document format input box, a document upload button, and an inspection result display area, which are used to receive the document format requirements and the document to be inspected by the user.

[0027] Document format requirements input box: Supports custom formatting rules (such as font, paragraph spacing, etc.), as well as general formatting rules and industry-specific rules (i.e. official document standards, academic paper formats, etc.).

[0028] Multi-format document upload interface: Supports multiple formats such as Docx, PDF, and TXT.

[0029] Inspection results visualization area: Errors are displayed in a highlighted and categorized list format, and a one-click repair function is provided.

[0030] The backend processing module 2002 is used to perform format analysis, basic misspelling recognition, and semantic misspelling recognition on the document to be checked according to the document format requirements and preset inspection rules through the format inspection unit, the basic misspelling recognition unit, and the AI-enhanced inspection unit, so as to obtain format inspection results, basic misspelling recognition results, and semantic misspelling recognition results.

[0031] The backend processing module is built on the Spring Boot framework and adopts a microservice architecture. It should be understood that the preset inspection rules can be parallel inspection rules (i.e., the format inspection unit, the basic misspelling recognition unit, and the AI-enhanced inspection unit process the document to be inspected at the same time), or sequential inspection rules (i.e., after the format inspection unit processes the document, the basic misspelling recognition unit processes the document, and after the basic misspelling recognition unit processes the document, the AI-enhanced inspection unit processes the document).

[0032] Furthermore, the preset inspection rule is a parallel inspection rule. Based on the document format requirements, the document to be inspected is simultaneously analyzed for format, identified for basic misspellings, and identified for semantic misspellings by the format inspection unit, the basic misspelling identification unit, and the AI-enhanced inspection unit, in accordance with the parallel inspection rule, so as to obtain the format inspection results, the basic misspelling identification results, and the semantic misspelling identification results.

[0033] Furthermore, the preset inspection rule is a sequential inspection rule. Based on the document format requirements, the format inspection unit performs format analysis on the document to be inspected. After the format analysis is completed, the format inspection result is obtained, and the basic misspelling recognition unit performs basic misspelling recognition on the document to be inspected. After the basic misspelling recognition is completed, the basic misspelling recognition result is obtained, and the AI-enhanced inspection unit performs semantic misspelling recognition on the document to be inspected to obtain the semantic misspelling recognition result.

[0034] It should also be noted that the format checking unit includes a multi-format parsing engine (i.e., a dedicated parser for different document types (Word / PDF / TXT)) and a layered checking strategy (i.e., first check the overall document structure (such as chapter settings), and then check the detailed format (such as font styles)). At the same time, the format checking unit supports complex format rules, such as multi-level heading styles and nested table format validation.

[0035] Furthermore, the processing method for performing format analysis on the document to be inspected by the format inspection unit is as follows: determine the document type of the document to be inspected; perform format parsing on the document to be inspected using the parser corresponding to the document type to obtain the overall structure and detailed format of the document to be inspected; determine the target format rules in the format database according to the document format requirements; and perform format analysis on the overall structure and detailed format based on the target format rules.

[0036] It should also be noted that when the format check unit performs format parsing on the document, it checks in a step-by-step and region-by-region manner. First, it checks the overall format of the document, and then it checks the detailed format.

[0037] The target format rules are custom format rules, general format rules, or industry-specific professional rules set by the user in the document format requirements input box.

[0038] In a specific implementation, the format check unit matches the overall structure and detailed format of the document to be checked with the target format rules in the format database according to a hierarchical check strategy. If the formats do not match, it generates a format error prompt message (i.e., the format check result) with the location of the format error, the incorrect format information, and the corresponding correct format information.

[0039] Furthermore, the processing method of the basic typo recognition unit for the document to be checked is as follows: It divides the document to be checked into task blocks through a document chapter division strategy; based on the multi-threaded scanning method, it uses multiple general typographical errors and multiple professional field typographical errors in the typo library to perform basic typo recognition on the divided task blocks through the basic typo recognition unit.

[0040] Multiple general typographical errors and multiple professional field typographical errors (such as professional terms in ship general, marine engineering, electrical, etc.) in the typo library. The document chapter division strategy is to divide multiple task blocks according to the document chapters.

[0041] Basic typo recognition unit: Multi-threaded scanning method: Processes multiple task blocks in parallel to improve the inspection speed.

[0042] Typo library dynamic update mechanism: Supports hot loading of newly added typographical errors.

[0043] Fuzzy matching function: Identifies similar-looking characters (such as "己" vs "已" vs "巳") and similar-sounding characters (such as "必须" vs "必需"), etc.

[0044] The basic typo recognition unit obtains all typographical errors from the typo library, traverses the entire document to be checked in a line-by-line and paragraph-by-paragraph manner, and matches each word in the document with the typographical errors; if a typo is matched, it records the location of the typo, the incorrect word, and the corresponding correct word, and generates a typo prompt message (i.e., the basic typo recognition result).

[0045] It should also be noted that the format checking unit accurately locates the specified position in the document according to the format requirements for format matching, and can accurately identify format errors; the basic typo recognition unit retrieves typo information from the typo database and traverses the entire document, ensuring the comprehensiveness and accuracy of typo recognition. The combination of these two units enables comprehensive document checking, improving the quality and efficiency of document processing and meeting the needs of practical applications.

[0046] Furthermore, the AI-enhanced inspection unit includes a text cleaning subunit and a semantic analysis subunit, with the semantic analysis subunit built based on the DeepSeek-R1 offline model.

[0047] The AI-enhanced inspection unit performs semantic misspelling recognition on the document to be inspected by extracting the text content of the document through the text cleaning subunit and then performing semantic misspelling recognition on the text content through the semantic analysis subunit.

[0048] DeepSeek-R1 offline model optimization deployment: Quantization strategy: INT8 / Q4_K_M hybrid quantization is used to compress the model size to 3.5GB while maintaining 98.2% accuracy.

[0049] Resource adaptation: Automatically select the optimal quantization scheme based on available memory (e.g., Q4_K_M for low-end devices and Q6_K for high-end devices).

[0050] In the specific implementation, the text cleaning unit is used to extract plain text content from the document to be checked, filter out format marks and special symbols, and then the semantic analysis subunit receives the plain text content after format checking, calls the DeepSeek local API to perform semantic-level typo analysis using quantitative inference technology, and returns a structured AI inspection result (i.e., semantic typo recognition result, including semantic error location, semantic error information and corresponding semantic correct information, confidence (i.e. semantic understanding confidence)). The interface has been reserved and more AI can be integrated in the future.

[0051] It should also be noted that the database module includes a format database and a typo database. The database module can use relational databases such as MySQL to store various preset document format templates and typo lists, facilitating querying and retrieval by the backend module.

[0052] In this embodiment, examples can be provided for reference. Figure 3 , Figure 3This is the module interaction flowchart of the first embodiment of the intelligent document inspection system of the present invention. When the user inputs the document format requirements as a custom format rule "the title font is bold, the font size is二号, and the first line of each paragraph is indented by 2 characters" on the front-end interface and uploads a document to be inspected, the front-end sends this information to the back-end.

[0053] The format inspection unit of the back-end first analyzes the document (for example, for a Word document, uses the corresponding parsing library to extract the format information of the document), finds the title part, checks whether its font and font size meet the requirements, and then checks whether the first line of each paragraph is indented by 2 characters. If it is found that the first line indentation of a certain paragraph does not meet the requirements, a format error prompt is generated.

[0054] The basic typo recognition unit obtains all typos from the typo library, and then traverses the full text of the document. When "辩别" is found, it should be "辨别", and a typo prompt message is generated.

[0055] Subsequently, the AI enhanced inspection module extracts the body content, calls the locally deployed DeepSeek model for in-depth analysis, identifies semantic errors such as "权利要求书" miswritten as "权利要求书", and suggests corrections with a confidence level of 90%.

[0056] The back-end processing module 2002 is further configured to classify and aggregate the format inspection result, the basic typo recognition result, and the semantic typo recognition result, generate a document modification prompt message, and send the document modification prompt message to the front-end interaction module 2001 for display.

[0057] Furthermore, the back-end processing module further includes a result fusion unit; the processing method for classifying and aggregating the format inspection result, the basic typo recognition result, and the semantic typo recognition result is: determining the confidence level corresponding to the semantic typo recognition result; when the confidence level is greater than the preset threshold, if there is an ambiguity between the basic typo recognition result and the semantic typo recognition result, the semantic typo recognition result shall prevail, and the basic typo recognition result and the semantic typo recognition result are integrated; the integrated typo recognition result and the format inspection result are classified and aggregated.

[0058] It should also be understood that when the confidence level is less than or equal to the preset threshold, if there is an ambiguity between the basic typo recognition result and the semantic typo recognition result, the basic typo recognition result shall prevail, and the basic typo recognition result and the semantic typo recognition result are integrated.

[0059] In this embodiment, the intelligent document inspection system includes a front-end interaction module and a back-end processing module. The front-end interaction module is built on the Vue2 framework, and the back-end processing module is built on the Spring Boot framework. The back-end processing module includes a format inspection unit, a basic misspelling recognition unit, and an AI-enhanced inspection unit. First, the front-end interaction module receives the document to be inspected and the corresponding document format requirements input by the user, and sends the document to be inspected and the document format requirements to the back-end processing module. Then, based on the document format requirements and according to preset inspection rules, the back-end processing module performs format analysis, basic misspelling recognition, and semantic misspelling recognition on the document to be inspected through the format inspection unit, the basic misspelling recognition unit, and the AI-enhanced inspection unit to obtain format inspection results, basic misspelling recognition results, and semantic misspelling recognition results. Afterward, the back-end processing module is also used to classify and aggregate the format inspection results, the basic misspelling recognition results, and the semantic misspelling recognition results, generate document modification prompt information, and send the document modification prompt information to the front-end interaction module for display. Compared to existing technologies that rely on manual inspection, which is inefficient and prone to errors, this embodiment improves the efficiency and accuracy of document inspection by combining rule matching and AI semantic analysis technologies.

[0060] Reference Figure 4 , Figure 4 This is a flowchart illustrating the first embodiment of the document intelligent inspection method of the present invention.

[0061] like Figure 4 As shown, the document intelligent inspection method proposed in this embodiment of the invention includes the following steps: Step S10: The front-end interaction module receives the document to be checked and the corresponding document format requirements input by the user, and sends the document to be checked and the document format requirements to the back-end processing module; Step S20: Based on the document format requirements, the backend processing module performs format analysis, basic misspelling recognition, and semantic misspelling recognition on the document to be checked according to preset inspection rules through the format inspection unit, the basic misspelling recognition unit, and the AI-enhanced inspection unit, so as to obtain format inspection results, basic misspelling recognition results, and semantic misspelling recognition results; Step S30: The backend processing module classifies and aggregates the format check results, the basic misspelling recognition results, and the semantic misspelling recognition results, generates document modification prompt information, and sends the document modification prompt information to the frontend interaction module for display.

[0062] Other embodiments or specific implementations of the document intelligent inspection method of the present invention can be found in the above-described system embodiments, and will not be repeated here.

[0063] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0064] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0065] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory / random access memory, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0066] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A document intelligent inspection system, characterized in that, The system includes a front-end interaction module and a back-end processing module. The front-end interaction module is built on the Vue2 framework, and the back-end processing module is built on the Spring Boot framework. The back-end processing module includes a format checking unit, a basic typo recognition unit, and an AI-enhanced checking unit. The front-end interaction module is used to receive the document to be checked and the corresponding document format requirements input by the user, and send the document to be checked and the document format requirements to the back-end processing module. The backend processing module is used to perform format analysis, basic misspelling recognition, and semantic misspelling recognition on the document to be checked according to the document format requirements and preset checking rules through the format checking unit, the basic misspelling recognition unit, and the AI-enhanced checking unit, so as to obtain format checking results, basic misspelling recognition results, and semantic misspelling recognition results; The backend processing module is also used to classify and aggregate the format check results, the basic misspelling recognition results and the semantic misspelling recognition results, generate document modification prompt information, and send the document modification prompt information to the frontend interaction module for display.

2. The system as described in claim 1, characterized in that, The preset inspection rule is a parallel inspection rule; Based on the document format requirements and according to preset inspection rules, the document to be inspected is analyzed for format, basic misspellings, and semantic misspellings using the format inspection unit, the basic misspelling recognition unit, and the AI-enhanced inspection unit to obtain format inspection results, basic misspelling recognition results, and semantic misspelling recognition results, including: Based on the document format requirements and in accordance with the parallel inspection rules, the document to be inspected is subjected to format analysis, basic misspelling recognition, and semantic misspelling recognition by the format inspection unit, the basic misspelling recognition unit, and the AI-enhanced inspection unit, respectively, to obtain format inspection results, basic misspelling recognition results, and semantic misspelling recognition results.

3. The system as described in claim 1, characterized in that, The preset inspection rule is a sequential inspection rule; Based on the document format requirements and according to preset inspection rules, the document to be inspected is analyzed for format, basic misspellings, and semantic misspellings using the format inspection unit, the basic misspelling recognition unit, and the AI-enhanced inspection unit to obtain format inspection results, basic misspelling recognition results, and semantic misspelling recognition results, including: Based on the document format requirements, the format checking unit performs format analysis on the document to be checked. After the format analysis is completed, the format check results are obtained, and the basic misspelling recognition unit is used to identify basic misspellings in the document to be checked. After the basic misspelling recognition is completed, the basic misspelling recognition result is obtained, and the AI-enhanced inspection unit performs semantic misspelling recognition on the document to be inspected to obtain the semantic misspelling recognition result.

4. The system according to any one of claims 1-3, characterized in that, The format analysis of the document to be inspected by the format inspection unit includes: Determine the document type of the document to be inspected; The document to be inspected is parsed using the parser corresponding to the document type to obtain the overall structure and detailed format of the document to be inspected. Determine the target format rules in the format database based on the document format requirements; The overall structure and the detailed format are analyzed based on the target format rules.

5. The system according to any one of claims 1-3, characterized in that, The basic misspelling recognition unit performs basic misspelling recognition on the document to be checked, including: The document to be inspected is divided into task blocks using a document chapter division strategy; Based on the multi-threaded scanning method, the basic misspellings of the divided task blocks are identified by the basic misspelling recognition unit, which uses multiple general misspellings and multiple professional misspellings in the misspelling library.

6. The system according to any one of claims 1-3, characterized in that, The AI-enhanced inspection unit includes a text cleaning subunit and a semantic analysis subunit, wherein the semantic analysis subunit is built based on the DeepSeek-R1 offline model. The AI-enhanced inspection unit performs semantic misspelling recognition on the document to be inspected, including: The text content of the document to be inspected is extracted through the text cleaning subunit; The semantic analysis subunit is used to identify semantic misspellings in the text content.

7. The system as described in claim 1, characterized in that, The backend processing module also includes a result fusion unit; The format check results, the basic misspelling recognition results, and the semantic misspelling recognition results are categorized and aggregated, including: Determine the confidence level corresponding to the semantic misspelling recognition result; When the confidence level is greater than a preset threshold, the basic misspelling recognition result and the semantic misspelling recognition result are integrated and processed. The integrated typo recognition results and the format check results are categorized and aggregated.

8. A document intelligent inspection method, characterized in that, The method includes the following steps: The front-end interaction module receives the document to be checked and the corresponding document format requirements input by the user, and sends the document to be checked and the document format requirements to the back-end processing module; The backend processing module performs format analysis, basic misspelling recognition, and semantic misspelling recognition on the document to be checked according to the document format requirements and preset inspection rules through the format inspection unit, the basic misspelling recognition unit, and the AI-enhanced inspection unit, so as to obtain format inspection results, basic misspelling recognition results, and semantic misspelling recognition results; The backend processing module classifies and aggregates the format check results, the basic misspelling recognition results, and the semantic misspelling recognition results, generates document modification prompts, and sends the document modification prompts to the frontend interaction module for display.

9. A document intelligent inspection device, characterized in that, The device includes: a memory, a processor, and a document intelligent inspection program stored in the memory and executable on the processor, the document intelligent inspection program being configured to implement the steps of the document intelligent inspection method as described in claim 8.

10. A storage medium, characterized in that, The storage medium stores a document intelligent inspection program, which, when executed by a processor, implements the steps of the document intelligent inspection method as described in claim 8.

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