Multi-user cooperation document processing method
By customizing user roles and permission matrices and combining deep learning models to analyze operational intentions, the problems of permission management and version conflicts in multi-person collaborative document processing are solved, achieving fine-grained control and efficient collaboration of documents.
Patent Information
- Application Number
- CN202510760903.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-09
- Publication Date
- 2025-09-19
AI Technical Summary
Existing multi-person collaborative document processing technologies are unable to achieve fine-grained control in terms of permission management, resulting in the accidental modification or leakage of important content, frequent and difficult-to-manage version conflicts, and affecting collaboration efficiency and security.
Through customized user roles, permission matrix configuration and deep learning model analysis of operational intentions, fine-grained permission control and intelligent version conflict resolution are achieved. Combined with visual difference display and universal intermediate format conversion, document security and integrity are ensured.
It achieves precise control of document permissions, reduces information security risks, improves the efficiency of version conflict resolution, ensures document format compatibility and integrity, and optimizes collaboration processes.
Smart Images
Figure CN120671204A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of computer software collaborative office technology, in particular to a multi-person collaborative document processing method. Background Art
[0002] To adapt to the diverse and professional needs of collaborative office scenarios within the enterprise, employees usually need to directly use clients and internal enterprise applications (such as official document systems) to realize functions such as creating, previewing, editing, leaving traces, saving, deleting, and version management of various document types such as text, tables, and presentations, thereby improving office efficiency.
[0003] In the field of computer software collaborative office technology, multi-person collaborative document processing technologies, represented by Google Docs and Office 365, have been widely used, significantly improving team collaboration efficiency. However, these technologies still have obvious flaws that seriously affect the collaborative experience and work quality.
[0004] In terms of permission management, existing technologies only provide a binary permission setting of "edit / view", which is difficult to meet the fine-grained control needs in complex collaborative scenarios. For example, in the collaborative preparation of corporate financial statements, ordinary employees are expected to be able to edit only designated worksheet data, while formulas and formats cannot be modified. However, binary permissions cannot achieve such precise control. When collaborating on academic papers, some participants need to be restricted to adding comments rather than directly modifying the main text. The existing permission management model is unable to address this. This extensive permission management method can not only lead to the accidental modification or leakage of important document content, but also increase information security risks due to excessive permission opening.
[0005] In terms of version management, version conflicts frequently occur when multiple people modify a document concurrently. Existing technologies typically rely on manual conflict resolution. For example, after editing a document, the system prompts a version conflict, requiring users to manually select which version to retain. However, this approach can easily overwrite content, leading to the loss of critical information and compromising the integrity and accuracy of the document. Frequent version conflicts and chaotic version records also make it difficult for team members to quickly and accurately trace the document's modification history and the differences between versions, significantly reducing work efficiency and increasing collaboration costs.
[0006] Therefore, a multi-person collaborative document processing method is proposed to solve the above-mentioned problems. Summary of the Invention
[0007] (1) Technical problems solved
[0008] In response to the shortcomings of the existing technology, the present invention provides a multi-person collaborative document processing method with the advantages of fine-grained permission control and intelligent version conflict resolution, solving the permission management problem: breaking through the traditional "edit / view" binary permission restrictions, through customized user roles, permission matrix configuration and permission inheritance rules, it realizes the refined permission allocation for specific areas and functions of the document, solves the problem of extensive permission control in complex scenarios such as corporate financial statement preparation and academic paper writing, avoids the accidental modification or leakage of important content, and reduces information security risks.
[0009] (2) Technical solution
[0010] To achieve the above-mentioned fine-grained permission control and intelligent version conflict resolution, the present invention provides the following technical solution: a multi-person collaborative document processing method, comprising the following steps:
[0011] S1: During the document creation phase, the creator customizes multiple user roles and can set detailed operation permissions for specific areas and different functions (text editing, annotation operations, format settings) of the document. Special permissions can also be set for individual users. Permission information is encrypted and stored, and change logs are recorded.
[0012] S2: When a user logs in to access a document, the system verifies the user's identity and dynamically displays or hides the user interface operation buttons based on their corresponding permissions;
[0013] S3: Multiple users can edit documents simultaneously. The system monitors the editing operations in real time, assigning unique identifiers and timestamps to each edit. A built-in deep learning model analyzes the operation intent and executes them sequentially if there are no conflicts. If there are conflicts, a preview of the versions is generated for authorized users to select, and the unselected versions are stored in the history library.
[0014] S4: The system automatically creates detailed version records for each document modification. Users can search by timeline or keyword through the version management interface, and view the version differences visually. It supports one-click restoration and records operation logs.
[0015] S5: During document upload and download, the system automatically identifies the format type and converts it into a common intermediate format for storage and processing. When downloading, it converts it into the target format according to user needs to ensure format consistency.
[0016] Preferably, the step of customizing and generating multiple user roles in S1 includes:
[0017] 1) The creator generates basic user roles based on a preset role template library, which includes editor, reviewer, commentator, and observer roles;
[0018] 2) Configure a permissions matrix for each user role, which contains permission bits for different document areas (sections, paragraphs, table cells) and operation types (edit, delete, copy, annotate, format settings);
[0019] 3) The selective overwriting of parent role permissions by child roles is achieved through permission inheritance rules, and permission information is stored in a distributed database using an asymmetric encryption algorithm.
[0020] Preferably, the step of analyzing the operation intention using a deep learning model in S3 includes:
[0021] Build an operation intention analysis model based on the Transformer architecture, with input including the operation context vector, operation type encoding, and operation position encoding;
[0022] The model outputs the probability distribution of operation intentions and calculates the probability of operation conflict using the following formula:
[0023]
[0024] Where Overlap(A, B) is the content overlap between operations A and B, and Size(A) is the impact range of operation A.
[0025] When P(conflict) exceeds the preset threshold, the version conflict resolution process is triggered.
[0026] Preferably, the step of visually displaying version differences in S4 includes:
[0027] 1) Using a line block-based difference calculation algorithm to decompose the document into semantic line block units;
[0028] 2) Use color coding to distinguish different types of changes: new content is highlighted with a green background, deleted content is marked with a red strikethrough, and modified content is displayed in left and right columns for comparison;
[0029] 3) Implement the change animation demonstration function, and dynamically display the evolution process of the document from the selected version to the current version through the timeline slider.
[0030] Preferably, the step of converting the universal intermediate format in S5 includes:
[0031] Parse the document content into an abstract syntax tree (AST) structure, wherein the AST contains text nodes, format nodes, structure nodes, and metadata nodes;
[0032] Using XSLT transformation rules to map documents of different formats into a unified intermediate XML format, the intermediate format uses a relative positioning system instead of absolute coordinates;
[0033] Implement bidirectional mapping function for format conversion:
[0034] Intermediate=ConvertToIntermediate(OriginalFormat, Metadata)
[0035] TargetFormat=ConvertToTarget(Intermediate, TargetSpec).
[0036] Preferably, the method further comprises an operational risk assessment step:
[0037] Establish a risk assessment model based on behavioral characteristics, with input parameters including operation frequency, operation duration, operation period, and operation content sensitivity coefficient;
[0038] The operational risk score is calculated using the following formula:
[0039]
[0040] Among them, w i is the weight of each feature, f i is the feature conversion function;
[0041] When the risk score exceeds the preset threshold, relevant operations are automatically restricted and the secondary authentication process is triggered.
[0042] Preferably, the step of the system verifying the user identity in S2 includes:
[0043] A multi-factor authentication mechanism is adopted, which includes at least two verification methods among dynamic verification codes, biometric recognition (fingerprint or face recognition), and hardware tokens; user identity information and permission information are hashed and stored, and the consistency of identity and permissions is verified through a public-private key encryption system during each verification; if the verification fails more than the preset number of times, the account will be automatically locked and an abnormal login alert will be sent to the administrator.
[0044] Preferably, the training step of the operation intention analysis model includes:
[0045] Collect at least 100,000 sets of editing operation data in real collaborative scenarios and label the operation intention categories (addition, modification, deletion, format adjustment); use transfer learning technology to fine-tune based on the pre-trained NLP model; optimize model parameters through the cross-entropy loss function, and stop training when the accuracy of the validation set reaches more than 95%; use the latest operation data for incremental training every week to update the model parameters.
[0046] Preferably, the visual display of version differences further includes:
[0047] Generates a version difference comparison report containing statistical data on each version change (number of new / deleted words, distribution of modified regions, and percentage of participating users' contributions); supports exporting reports in PDF format, embeds hyperlinks in the report, and clicks to jump directly to the corresponding modified location in the document; provides a shared link for version difference comparison, through which authorized users can quickly view detailed changes between specified versions.
[0048] (3) Beneficial effects
[0049] Compared with the prior art, the present invention provides a multi-person collaborative document processing method with the following beneficial effects:
[0050] 1. This multi-person collaborative document processing method achieves fine-grained control of document permissions through customized user roles, configured permission matrix, and dynamic interface display, accurately adapting to the needs of complex collaborative scenarios and effectively avoiding the risk of misoperation of important content and information leakage.
[0051] 2. This multi-person collaborative document processing method, with the help of deep learning models to intelligently analyze operational intentions, visualize version difference tracing, and universal intermediate format conversion technology, significantly improves the efficiency of version conflict resolution and document format compatibility in multi-person collaboration, optimizes the collaboration process, and ensures document integrity. BRIEF DESCRIPTION OF THE DRAWINGS
[0052] Figure 1 This is a flow chart of the multi-person collaborative document processing method of the present invention. DETAILED DESCRIPTION
[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.
[0054] Example 1
[0055] See also Figure 1 , a multi-person collaborative document processing method includes the following steps:
[0056] S1: During the document creation phase, the creator customizes multiple user roles and can set detailed operation permissions for specific areas and different functions (text editing, annotation operations, format settings) of the document. Special permissions can also be set for individual users. Permission information is encrypted and stored, and change logs are recorded.
[0057] S2: When a user logs in to access a document, the system verifies the user's identity and dynamically displays or hides the user interface operation buttons based on their corresponding permissions;
[0058] S3: Multiple users can edit documents simultaneously. The system monitors the editing operations in real time, assigning unique identifiers and timestamps to each edit. A built-in deep learning model analyzes the operation intent and executes them sequentially if there are no conflicts. If there are conflicts, a preview of the versions is generated for authorized users to select, and the unselected versions are stored in the history library.
[0059] S4: The system automatically creates detailed version records for each document modification. Users can search by timeline or keyword through the version management interface, and view the version differences visually. It supports one-click restoration and records operation logs.
[0060] S5: During document upload and download, the system automatically identifies the format type and converts it into a common intermediate format for storage and processing. When downloading, it converts it into the target format according to user needs to ensure format consistency.
[0061] In this embodiment, this method designs a series of innovative steps to address the problems of existing multi-person collaborative document processing technologies in permission management, version conflicts and format compatibility. In permission management, S1 implements precise permission management and ensures information security through customized user roles and fine-grained permission settings, combined with S2 dynamically displaying operation buttons; in version management, S3 uses deep learning models to intelligently resolve version conflicts, and S4 provides detailed version records and visual difference displays to effectively avoid content loss and improve version tracing efficiency; to address the problem of format compatibility, S5 uses a universal intermediate format conversion to ensure that documents are consistent in format on different devices and software.
[0062] These steps work together to optimize the multi-person collaborative document processing process from multiple dimensions. They not only solve the pain points of traditional technologies such as extensive permissions, version confusion, and formatting errors, but also significantly improve collaboration standardization, document integrity, and work efficiency, providing enterprises and teams with more efficient, secure, and stable document collaboration solutions.
[0063] Example 2
[0064] Multi-person collaborative document processing method based on information sharing
[0065] The following is a step-by-step description of an embodiment combining the claims with specific scenarios, taking the collaboration of a company's new product development project plan as an example:
[0066] S1: Document creation and permission customization
[0067] 1.1) Role template library call
[0068] The project leader logs into the system, creates a "New Product R&D Project Plan" document, and selects basic roles (such as editor, reviewer, commentator, observer) from the preset role template library.
[0069] 1.2) Permission Matrix Configuration
[0070] 1.21) Assign full permissions to the "Project Manager" role: edit all chapters, modify formatting, manage comments, and view change logs;
[0071] 1.22) Set limited permissions for the "Finance Specialist": only edit data cells in the "Budget Planning" table, and prohibit modifying formulas and formats;
[0072] 1.22) Configure special permissions for "Technical Consultant": only have editing rights to the "Technical Solution" section, can add comments but cannot delete other people's content.
[0073] 1.3) Fine-grained permission coverage
[0074] For new members, separate permissions are set based on the "Planning Specialist" role: they are restricted to viewing data charts in the "Market Analysis" section and have no editing rights.
[0075] 1.4) Permission Encrypted Storage
[0076] The system encrypts all permission information using an asymmetric encryption algorithm (such as RSA), stores it in a distributed database (such as MongoDB), and records permission change logs (including operation time, operator, and change content).
[0077] S2: Authentication and Dynamic Interface
[0078] 2.1) Multi-factor authentication
[0079] 2.11) When logging in, users must provide:
[0080] 2.12) Account and Password
[0081] 2.13) Dynamic verification code (obtained via SMS)
[0082] 2.14) Fingerprint recognition (if supported by the device)
[0083] 2.2) Permissions and interface binding
[0084] The system verifies the consistency of user identity and permissions through a public-private key encryption system, and dynamically displays / hides operation buttons based on user roles:
[0085] 2.21) Planners only see the edit button for the "Planning Scheme" section, and the formatting toolbar is hidden;
[0086] 2.22) Reviewers only see the "View" and "Annotate" buttons, with no editing options.
[0087] S3: Real-time editing and intelligent conflict handling
[0088] 3.1) Operation Identifier and Timestamp Allocation
[0089] When multiple users edit simultaneously, the system assigns a unique identifier (such as OP-20230530-001) and a timestamp accurate to milliseconds to each operation.
[0090] 3.2) Operation Intention Analysis
[0091] The deep learning model based on the Transformer architecture analyzes operational intent in real time. Input parameters include:
[0092] 3.21) Operation context vector (such as the context before and after the edit position)
[0093] 3.22) Operation type code (add, modify, delete, etc.)
[0094] 3.23) Manipulate position codes (chapter, paragraph, line number)
[0095] 3.3) Conflict Probability Calculation and Resolution
[0096] When concurrent operations are detected, the system calculates the probability of conflict:
[0097]
[0098] If the probability exceeds the threshold (such as 0.7), the system generates two version previews, highlights the conflicting parts in different colors, and pushes them to the project manager for decision-making. The unadopted version is stored in the history library.
[0099] S4: Version management and visual traceability
[0100] 4.1) Automatic version recording
[0101] Each modification automatically generates a version number (e.g., V1.0.202305301430), records the modifier, modification time, and modification summary (e.g., "Update market analysis data");
[0102] 4.2) Timeline and keyword search
[0103] Users can select historical versions using the timeline slider or enter keywords (such as "initial budget") to quickly locate relevant versions;
[0104] 4.3) Visualization of differences
[0105] 4.31) New: Green background highlight
[0106] 4.32) Deleted content: marked with a red strikethrough
[0107] 4.33) Modified content: Compare the left and right columns, and mark the changes in yellow
[0108] 4.4) One-click restore and audit
[0109] After the user selects a historical version, the system generates a restore preview. After confirmation, the restore operation is performed and an operation log is recorded (including the restorer and the comparison of the versions before and after the restore).
[0110] S5: Format compatibility processing
[0111] 5.1) Intermediate format conversion
[0112] When a user uploads a document, the system automatically parses it into an abstract syntax tree (AST), converts it into a unified intermediate XML format for storage, and retains text nodes, format nodes, structure nodes, and metadata.
[0113] 5.2) Bidirectional mapping function
[0114] 5.21) When uploading:
[0115] Intermediate=ConvertToIntermediate(OriginalFormat, Metadata)
[0116] 5.22) When downloading:
[0117] TargetFormat=ConvertToTarget(Intermediate, TargetSpec).
[0118] For example, when users upload documents from Word, they can choose to convert them into PDF, Excel and other formats when downloading. The system ensures that the table layout, font style, etc. remain consistent.
[0119] S6: Operational Risk Assessment (Supplementary Step)
[0120] 6.1) Risk model parameter collection
[0121] The system monitors user operations in real time and collects parameters:
[0122] 6.11) Operation frequency (e.g. 10 consecutive modifications within 5 minutes)
[0123] 6.12) Operation duration (e.g., modifying sensitive data at 2 a.m.)
[0124] 6.13) Operational content sensitivity (such as involving financial data, core technology)
[0125] 6.2) Risk Score Calculation
[0126] The risk score is calculated using the formula:
[0127] When the score exceeds the threshold (such as 80 points), the operation is automatically restricted and a secondary verification (such as face recognition + SMS verification code) is triggered.
[0128] S7: Extended Functionality Implementation
[0129] 7.1) Model training optimization
[0130] The development team regularly collects more than 100,000 sets of real collaboration data, labels the operation intention categories (new additions, modifications, etc.), fine-tunes the operation intention analysis model based on the pre-trained BERT model, and deploys it online after the verification set accuracy reaches 95%, and updates the parameters through incremental training every week.
[0131] 7.2) Difference report generation
[0132] The system automatically generates a version comparison report, including:
[0133] 7.21) Add / delete word count
[0134] 7.22) Modify the regional heat map (divided by chapter and paragraph)
[0135] 7.23) User contribution analysis (e.g., “John: 45%, John: 30%)
[0136] The report can be exported to PDF, and embedded hyperlinks can jump to specific locations in the document.
[0137] This multi-person collaborative document processing method is comprehensively optimized to address the shortcomings of traditional technologies. By customizing user roles and permission matrices, it breaks the limitations of the "edit / view" binary permission system and achieves precise control over specific areas and functions of documents. By analyzing operational intent with the help of deep learning models, the efficiency of version conflict resolution is improved, significantly reducing the cost of manual intervention. Relying on universal intermediate format conversion and two-way mapping functions, it achieves high accuracy in cross-platform format conversion and eliminates hidden dangers of format errors. Supplemented by an operational risk assessment mechanism, it builds a solid security line for document collaboration and comprehensively improves collaboration efficiency and information security.
[0138] In summary, this multi-person collaborative document processing method achieves fine-grained control of document permissions through customized user roles, configured permission matrix and dynamic interface display, accurately adapts to the needs of complex collaborative scenarios, and effectively avoids the risk of misoperation of important content and information leakage.
[0139] In addition, with the help of deep learning models to intelligently analyze operational intentions, visualize version difference tracing, and universal intermediate format conversion technology, the efficiency of version conflict resolution and document format compatibility in multi-person collaboration have been significantly improved, optimizing the collaboration process and ensuring document integrity.
[0140] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.
[0141] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.
Claims
1. A multi-person collaborative document processing method, characterized by: The following steps are involved: S1: During the document creation phase, the creator customizes multiple user roles and can set detailed operation permissions for specific areas and different functions (text editing, annotation operations, format settings) of the document. Special permissions can also be set for individual users. Permission information is encrypted and stored, and change logs are recorded. S2: When a user logs in to access a document, the system verifies the user's identity and dynamically displays or hides the user interface operation buttons based on their corresponding permissions; S3: Multiple users can edit documents simultaneously. The system monitors the editing operations in real time, assigning unique identifiers and timestamps to each edit. A built-in deep learning model analyzes the operation intent and executes them sequentially if there are no conflicts. If there are conflicts, a preview of the versions is generated for authorized users to select, and the unselected versions are stored in the history library. S4: The system automatically creates detailed version records for each document modification. Users can search by timeline or keyword through the version management interface, and view the version differences visually. It supports one-click restoration and records operation logs. S5: During document upload and download, the system automatically identifies the format type and converts it into a common intermediate format for storage and processing. When downloading, it converts it into the target format according to user needs to ensure format consistency.
2. The multi-person collaborative document processing method according to claim 1, characterized in that: The steps of customizing and generating multiple user roles in S1 include: 1) The creator generates basic user roles based on a preset role template library, which includes editor, reviewer, commentator, and observer roles; 2) Configure a permissions matrix for each user role, which contains permission bits for different document areas (sections, paragraphs, table cells) and operation types (edit, delete, copy, annotate, format settings); 3) The selective overwriting of parent role permissions by child roles is achieved through permission inheritance rules, and permission information is stored in a distributed database using an asymmetric encryption algorithm.
3. The multi-person collaborative document processing method according to claim 1, characterized in that: The steps of analyzing the operation intention using the deep learning model in S3 include: Build an operation intention analysis model based on the Transformer architecture, with input including the operation context vector, operation type encoding, and operation position encoding; The model outputs the probability distribution of operation intentions and calculates the probability of operation conflict using the following formula: Where Overlap(A, B) is the content overlap between operations A and B, and Size(A) is the impact range of operation A. When P(conflict) exceeds the preset threshold, the version conflict resolution process is triggered.
4. The multi-person collaborative document processing method according to claim 1, characterized in that: The step of visually displaying the version differences in S4 includes: 1) Using a line block-based difference calculation algorithm to decompose the document into semantic line block units; 2) Use color coding to distinguish different types of changes: new content is highlighted with a green background, deleted content is marked with a red strikethrough, and modified content is displayed in left and right columns for comparison; 3) Implement the change animation demonstration function, and dynamically display the evolution process of the document from the selected version to the current version through the timeline slider.
5. The multi-person collaborative document processing method according to claim 1, characterized in that: The steps of converting the common intermediate format in S5 include: Parse the document content into an abstract syntax tree (AST) structure, wherein the AST contains text nodes, format nodes, structure nodes, and metadata nodes; Using XSLT transformation rules to map documents of different formats into a unified intermediate XML format, the intermediate format uses a relative positioning system instead of absolute coordinates; Implement bidirectional mapping function for format conversion: Intermediate=ConvertToIntermediate(OriginalFormat, Metadata) TargetFormat=ConvertToTarget(Intermediate, TargetSpec).
6. The multi-person collaborative document processing method according to claim 1, characterized in that: The method further comprises the step of conducting risk assessment: Establish a risk assessment model based on behavioral characteristics, with input parameters including operation frequency, operation duration, operation period, and operation content sensitivity coefficient; The operational risk score is calculated using the following formula: Among them, w i is the weight of each feature, f i is the feature conversion function; When the risk score exceeds the preset threshold, relevant operations are automatically restricted and the secondary authentication process is triggered.
7. The multi-person collaborative document processing method according to claim 1, characterized in that: The steps of verifying the user's identity in S2 include: A multi-factor authentication mechanism is adopted, which includes at least two verification methods among dynamic verification codes, biometric recognition (fingerprint or face recognition), and hardware tokens; user identity information and permission information are hashed and stored, and the consistency of identity and permissions is verified through a public-private key encryption system during each verification; if the verification fails more than the preset number of times, the account will be automatically locked and an abnormal login alert will be sent to the administrator.
8. The multi-person collaborative document processing method according to claim 3, characterized in that: The training steps of the operation intention analysis model include: Collect at least 100,000 sets of editing operation data in real collaborative scenarios and label the operation intention categories (addition, modification, deletion, format adjustment); use transfer learning technology to fine-tune based on the pre-trained NLP model; optimize model parameters through the cross-entropy loss function, and stop training when the accuracy of the validation set reaches more than 95%; use the latest operation data for incremental training every week to update the model parameters.
9. The multi-person collaborative document processing method according to claim 4, characterized in that: The visual display of version differences also includes: Generates a version difference comparison report containing statistical data on each version change (number of new / deleted words, distribution of modified regions, and percentage of participating users' contributions); supports exporting reports in PDF format, embeds hyperlinks in the report, and clicks to jump directly to the corresponding modified location in the document; provides a shared link for version difference comparison, through which authorized users can quickly view detailed changes between specified versions.