An interactive manual data management method and system

Abstract

The present application relates to the technical field of data management, in particular to an interactive manual data management method and system, comprising the following steps: identifying field attribute variation and structure split nodes based on semantic label content, optimizing path structure in combination with actual application scenarios and user operation trajectories, analyzing path priority and identifying key path members, tracking field structure changes, and generating node chain encoding information. In the present application, automatic mapping of manual content structure is realized through semantic difference discrimination, path ordering is dynamically adjusted in combination with user behavior trajectory, path screening and grouping are completed based on behavior sequence characteristics for priority discrimination, field structure variation parameters refine influencing factors in collaborative editing and chain reference scenarios, forming a traceable and differentiable data circulation mode, and data retrieval and version management have flexible expansion capability, adapting to the multi-dimensional management and control needs of high concurrency, multiple changes and complex reference chains in manual scenarios.

Description

Technical Field

[0001] This invention relates to the field of data management technology, and in particular to an interactive manual data management method and system. Background Technology

[0002] Data management involves the orderly organization, storage, maintenance, and retrieval of information, including the cataloging of structured and unstructured data, data lifecycle management, data access control, version tracking, and metadata recording. It is widely used in enterprise knowledge base management, information archive systems, digital libraries, product technical document management, and technical support platforms, aiming to ensure the integrity, accessibility, and manageability of data resources. Traditional interactive manual data management methods refer to a user-oriented approach where users browse, search, and reference structured or semi-structured technical documents through a computer interface. This approach focuses on how to efficiently organize and interact with large amounts of manual-type data in different application scenarios.

[0003] Existing technologies employ static structures and template-based archiving methods, lacking responsiveness to semantic hierarchy evolution and dynamic adjustment mechanisms for behavioral paths. In practice, when faced with frequent changes in data structures and collaborative scenarios, static organization strategies are less able to capture real-time relationships between fields, leading to path solidification, slow response, and difficulty in mapping complex collaboration histories through chain node evolution. This can easily cause problems such as retrieval difficulties, data chain breakpoints, and version confusion, reducing the ability to collaborate and manage data efficiently in environments such as technical documents and knowledge bases. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide an interactive manual data management method and system. The technical solution is as follows:

[0005] On the one hand, an interactive manual data management method is provided, including the following steps:

[0006] S1: Based on semantic tag content, identify the direction of attribute change between fields, compare the relationship between adjacent fields, determine semantic structure changes, determine structural segmentation nodes, and obtain a set of structural breakpoint mappings;

[0007] S2: Based on the structure breakpoint mapping set, determine the application scenario of the manual data structure, analyze the user's operation sequence in paragraph structure fields and jump chains, aggregate operation trajectories, identify high-frequency nodes, and obtain path sequence association indicators.

[0008] S3: Based on the path sequence association index, analyze the positional characteristics of the path in the sequence, compare the differences in behavior patterns between high-frequency paths and other paths, determine the priority response path, and summarize the priority response path members to obtain the path priority identification set.

[0009] S4: Based on the path priority identification set, analyze the distribution of related fields in the manual structure, compare the current field with the historical structure hierarchy changes, determine whether the structure classification has been adjusted, identify the fields that have undergone classification changes, and obtain the field structure change parameters.

[0010] S5: Based on the field structure change parameters, analyze the node trajectory of the multi-user concurrent editing field and the reference chain structure field, identify frequently changing nodes, and adjust the chain index in combination with identity and time point to obtain node chain encoding information.

[0011] On the other hand, the structural breakpoint mapping set includes segmentation interval number, node positioning attribute, and structural classification code; the path sequence association index includes node sequence identifier, path aggregation attribute, and behavior pattern code; the path priority identification set includes priority label, path group member, and response category number; the field structure change parameter includes hierarchical adjustment item, classification change item, and impact degree item; and the node chain encoding information includes node number, link sequence, and edit information index.

[0012] On the other hand, the specific steps for obtaining the structural breakpoint mapping set are as follows:

[0013] S101: Based on semantic tag content, compare the keyword matching degree of adjacent fields and the direction of topic category change, determine the changes in semantic expression and classification attributes of field pairs, identify field pairs that have changed in semantic description and keyword coverage, and obtain the field semantic difference sequence.

[0014] S102: Based on the semantic difference sequence of the fields, determine the functional definition items and business process markers of each field, analyze the continuous changes between functional classification numbers, compare the sequential connection status of business process markers, identify the field sequence numbers where the functional classifications are different and the connection of process markers is interrupted, and obtain the node boundary marker group.

[0015] S103: Based on the node boundary identifier group, compare the semantic structure classification label and the structural hierarchy label, analyze the classification encoding span and hierarchy label jump of the fields before and after the node, determine the nodes where the classification attribute and hierarchy label change simultaneously, and obtain the structural breakpoint mapping set.

[0016] On the other hand, the specific steps for obtaining the path sequence association index are as follows:

[0017] S201: Based on the structure breakpoint mapping set, analyze the classification codes of each structure segmentation node and field, compare the category distribution of the corresponding fields in the paragraph structure, determine the mapping changes of the fields in the semantic classification of paragraph titles, descriptions and operation instructions, identify the fields with different distributions in the mapping relationship, and obtain the paragraph jump sequence feature set.

[0018] S202: Based on the paragraph jump sequence feature set, aggregate user field jump paths, calculate the access frequency of fields in each path, analyze the behavior changes of fields during paragraph jumps, identify the field numbers with high-frequency access and clustered behavior, and obtain the node access spectrum set.

[0019] S203: Based on the node access spectrum set, analyze the access order of adjacent nodes in the jump path, optimize the arrangement of nodes that are repeated or have changes in combination in the jump order, and obtain the path sequence association index by combining the combination relationship between nodes and the structural adjustment action.

[0020] On the other hand, the steps for obtaining the path priority identification set are as follows:

[0021] S301: Based on the path sequence association index, compare the start order and end node of each path in the jump sequence, determine the arrangement characteristics of the path in the sorting structure, and optimize the path arrangement by combining the number and order distribution of relay nodes in the path to obtain path stage distribution data.

[0022] S302: Based on the path stage distribution data, analyze the behavioral differences between frequently operated paths and other paths in terms of the number of jump behaviors, path structure, and node repetition phenomena, identify path numbers with concentrated access frequency and matching behavior patterns, and obtain the path priority response set;

[0023] S303: Based on the path priority response set, determine the grouping characteristics of the path number in the response sequence, analyze the consistency of the same group of paths in terms of jump direction, access density and operation order, aggregate the same type of paths according to the response category number, summarize the path combination members and response categories, and obtain the path priority identification set.

[0024] On the other hand, the specific steps for obtaining the field structure change parameters are as follows:

[0025] S401: Based on the path priority identification set, analyze the priority labels and path group members, determine the distribution status of the fields corresponding to each path in the manual structure hierarchy, compare the changes in the field classification labels between the codes of each structure hierarchy, identify the fields whose classification labels have changed, and obtain the structure hierarchy change index.

[0026] S402: Based on the structural hierarchical change index, compare the classification label with the structural level code, determine the correspondence between the current classification and the existing structural level, analyze the structural distribution differences between the classification change field and other fields in the manual, identify the field number of the structural distribution change, and obtain the classification change related data.

[0027] S403: Based on the aforementioned attribution change association data, analyze the distribution and impact range of the change fields in the manual's structural hierarchy, optimize the criteria for determining the field's impact range, adjust the impact distribution parameters of the classification change fields, and obtain the field structure change parameters.

[0028] On the other hand, the steps for obtaining the node chain encoding information are as follows:

[0029] S501: Based on the field structure change parameters, compare the hierarchical distribution and classification status of the fields involved in the manual structure, determine the changes of the fields between each structural node, identify the fields whose status has changed after the structural hierarchy adjustment or classification change, and obtain the hierarchical offset node group.

[0030] S502: Based on the hierarchical offset node group, determine the node trajectory of multi-user concurrent editing operations and reference chain structure fields, compare the frequency and position of content changes of nodes during editing and referencing, identify nodes with more changes, and obtain the node evolution trajectory group.

[0031] S503: Based on the node evolution trajectory group, combined with the operator's identity and time point, adjust the differentiation criteria of the node chain structure, analyze the editing order and differentiation path of each node in the link, optimize the indexing method according to the relationship between the node trajectory and the link, and obtain the node chain encoding information.

[0032] On the other hand, the semantic tag content refers to the semantic description, keywords and classification tags carried by each field in the manual, and the attribute change direction refers to the trend and direction of the semantic content change between two adjacent fields.

[0033] On the other hand, the manual data structure refers to the ordered relationship and data hierarchy among all fields, paragraphs and nodes in the manual, and the application scenario refers to the business process, role requirements or purpose of use when the user is using the manual.

[0034] On the other hand, an interactive manual data management system is provided, which is applied to an interactive manual data management method, including:

[0035] The structure segmentation module identifies the direction of attribute changes between fields based on semantic tag content, compares the relationship between adjacent fields, judges semantic structure changes, determines structure segmentation nodes, and obtains a set of structure breakpoint mappings.

[0036] Based on the structure breakpoint mapping set, the path aggregation module determines the application scenario of the manual data structure, analyzes the user's operation sequence in paragraph structure fields and jump chains, aggregates operation trajectories, identifies high-frequency nodes, and obtains path sequence association indicators.

[0037] Based on the path sequence association index, the priority path module analyzes the positional characteristics of the path in the sequence, compares the differences in behavior patterns between high-frequency paths and other paths, determines the priority response path, and summarizes the priority response path members to obtain the path priority identification set.

[0038] Based on the path priority identification set, the structural change module analyzes the distribution of related fields in the manual structure, compares the current field with the historical structural hierarchy changes, determines whether the structural classification has been adjusted, identifies the fields that have undergone classification changes, and obtains the field structure change parameters.

[0039] Based on the field structure change parameters, the node tracking module analyzes the node trajectory of the multi-user concurrent editing field and the reference chain structure field, identifies frequently changing nodes, and adjusts the chain index in combination with identity and time point to obtain node chain encoding information.

[0040] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0041] Automatic mapping of the manual's content structure is achieved through semantic difference discrimination. The path sorting is dynamically adjusted based on user behavior trajectory. Priority discrimination completes path filtering and grouping based on behavioral sequence features. Field structure change parameters refine the influencing factors in collaborative editing and chained referencing scenarios. The node chain encoding strategy maps the data evolution link in a way that links identity and time sequence, forming a traceable and differentiated data circulation model. Data retrieval and version management have flexible expansion capabilities, adapting to the multi-dimensional management needs of high concurrency, multiple changes, and complex referencing chains in manual scenarios, and promoting the transformation of data management towards behavior-driven and structure-adaptive directions. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart of the main steps of the present invention;

[0044] Figure 2 This is a flowchart of steps S1 of the present invention;

[0045] Figure 3 This is a flowchart of steps S2 of the present invention;

[0046] Figure 4 This is a flowchart of steps S3 of the present invention;

[0047] Figure 5 This is a flowchart of step S4 of the present invention;

[0048] Figure 6 This is a flowchart of steps S5 of the present invention;

[0049] Figure 7 This is a system block diagram of the present invention. Detailed Implementation

[0050] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0051] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0052] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0053] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0054] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0055] This invention provides an interactive manual data management method, such as... Figure 1 As shown, it includes the following steps:

[0056] S1: Based on semantic tag content, identify the direction of semantic attribute change between fields, compare the attribute relationship between adjacent fields, determine the semantic structure change between fields, identify the position of change as the structure segmentation node, and perform classification in combination with semantic structure to obtain the structure breakpoint mapping set.

[0057] S2: Based on the structural breakpoint mapping set, determine the actual application scenario of the manual data structure, analyze the user's operation order in paragraph structure fields and field jump chains, aggregate user operation trajectory, identify nodes with frequent behavior in the operation, optimize the arrangement of operation path, and adjust the path structure in combination with the behavior patterns between nodes to obtain path sequence association index.

[0058] S3: Based on the path sequence association index, analyze the position characteristics of each path in the sorting sequence, compare the differences in behavior patterns between frequently operated paths and other paths, determine the priority response category paths, and combine the grouping characteristics of the path response sequence to summarize the priority response path members and obtain the path priority identification set.

[0059] S4: Based on the path priority identification set, analyze the distribution of related fields in the manual structure, compare the changes of the current field with the historical structure hierarchy, determine whether the field structure classification has been adjusted, identify the fields whose classification has changed, optimize the field influence range judgment criteria, determine the influence magnitude, and obtain the field structure change parameters.

[0060] S5: Based on the field structure change parameters, determine the structural changes of the fields involved, analyze the node trajectory of fields edited concurrently by multiple users and fields in the reference chain structure, identify operation nodes with frequent structural changes, optimize the node differentiation standard, and adjust the field chain indexing method in combination with the operator's identity and time point to obtain the node chain encoding information.

[0061] The structural breakpoint mapping set includes segmentation interval number, node location attribute, and structural classification code; the path sequence association index includes node sequence identifier, path aggregation attribute, and behavior pattern code; the path priority identification set includes priority label, path group member, and response category number; the field structure change parameters include hierarchy adjustment item, classification change item, and impact degree item; and the node chain encoding information includes node number, link sequence, and edit information index.

[0062] In S1, semantic tag content refers to the semantic descriptions, keywords, and classification tags carried by each field in the manual, which are often used to indicate the actual meaning and business purpose of the field (such as "operation steps", "precautions", "parameter name"); the direction of semantic attribute change refers to the trend and direction of the semantic content change between two adjacent fields, mainly used to depict the differences in theme, purpose, and category, such as "description" becoming "operation instructions"; attribute relationship refers to the degree of functional or semantic association between adjacent fields, such as fields belonging to the same business process having a strong attribute relationship; semantic structure change refers to a significant change in the field sequence in terms of content, business logic, and functional type, such as transitioning from "chapter description" to "parameter definition"; structural segmentation nodes refer to the positions detected based on semantic changes that are suitable for logically segmenting the manual content for subsequent structured processing; semantic structure refers to the content architecture and logical system composed of each field and its semantic attributes in the overall manual.

[0063] In S2, the manual data structure refers to the ordered relationship and data hierarchy among all fields, paragraphs, and nodes in the manual, reflecting the organization of the manual content; the application scenario refers to the business process, role requirements, or purpose of use when users actually use the manual, such as new employees consulting operation guidelines or technical personnel searching for parameter descriptions; the paragraph structure field refers to the field content in the manual that has a clear paragraph affiliation, such as "Introduction" or "Methods and Steps"; the field jump chain refers to the field jump path and order formed by users in the process of consulting, jumping, and searching the manual content, such as "jumping from the table of contents to a certain chapter"; the user operation trajectory refers to the access order and operation process record of each field and functional module in the actual operation of the manual; the frequently used node refers to the specific field or node that is repeatedly accessed, clicked, or edited in a large number of user operation trajectories; the arrangement method refers to the way of sorting and reorganizing high-frequency nodes or paths to adapt to the actual operation flow requirements; the behavior pattern refers to the behavioral patterns or habits of users in the process of using the manual, such as first viewing the process overview and then consulting specific parameters; the path structure refers to the field jump path and overall link structure optimized based on the above behaviors and nodes.

[0064] In S3, the positional characteristics in the sorted sequence refer to the positional attributes of each path in the overall sequence after the path behavior is sorted, such as first, last, middle, etc., used to analyze its importance; frequently operated paths refer to path links that are frequently accessed, jumped to, or edited by users in the sorting; other paths refer to paths with lower user access frequency compared to high-frequency paths; priority response category paths refer to paths that are identified as needing priority response and fast presentation after comparison and analysis; grouping characteristics refer to the characteristics of classifying and grouping paths according to factors such as similarity, function, and access patterns; priority response path members refer to the entire set of paths classified into the priority response group.

[0065] In S4, "related fields" refers to fields that are closely related to the current path, operation, or scenario, and that have changed or been affected; "historical structure hierarchy" refers to the level, position, and classification of a field in previous versions of the manual, used for comparison with the current structure; "fields whose classification has changed" refers to fields whose classification or hierarchical position has changed after the structure or content has been updated; "field impact scope judgment criteria" refers to the criteria used to determine whether a field change affects the overall structure or the field itself, such as affecting link length, data dependencies, etc.; and "impact magnitude" refers to the specific size and scope of the impact brought about by the field structure change after judgment.

[0066] In S5, multi-user concurrent editing fields refer to scenarios where multiple users perform operations such as adding, deleting, and modifying the same field in the manual at the same time, emphasizing collaboration and conflict detection; reference chain structure fields refer to fields in the manual whose content is referenced or called multiple times by other fields, forming a chain reference relationship; node trajectory refers to the evolution path and historical change chain of a field or node during multiple editing and referencing processes; frequently changing operation nodes refer to fields or nodes with many change records and obvious content fluctuations in the node trajectory; node differentiation criteria refer to the judgment rules for determining whether a node has differentiated into an independent node due to changes, such as judging it as a new node if the content change exceeds a certain range; field chain indexing method refers to the method of generating a chain structure and index number for all nodes and fields according to the editing order, differentiation status, etc.

[0067] like Figure 2 As shown, the specific steps for obtaining the structural breakpoint mapping set are as follows:

[0068] S101: Based on semantic tag content, compare the keyword matching degree of adjacent fields and the direction of topic category change, determine the changes in semantic expression and classification attributes of field pairs, identify field pairs that have changed in semantic description and keyword coverage, and obtain the field semantic difference sequence.

[0069] Based on the semantic tags attached to the fields, the keyword content of each field is extracted sequentially. The keywords are decomposed and grouped into strings, forming independent keyword lists for each pair of adjacent fields. The keywords in the two lists are then compared pairwise to check for semantically similar words. The matching ratio is obtained by calculating the ratio of the number of similar words to the total number of keywords. This ratio is compared with a preset range. A ratio between 0.3 and 0.65 is considered a moderate match, while a ratio below 0.3 is considered a poor match. The topic category names of the two fields are then extracted and mapped to the type classification items in the given business scenario. For example, if one field's topic is "preparation work" and the other is "operation instructions," the former is marked as the preparation category and the latter as the execution category. Based on the category order from preparation to execution, the category direction is determined to be a downward progression. Finally, the semantic description content of the two fields is extracted, and the descriptive text is divided into... After collecting the sentences, each sentence is compared to see if it contains directive words, explanatory words, and technical terms. The frequency of each type of word in the field is counted, and the degree of difference in the descriptive structure of the two fields is compared by the frequency ratio. For example, if one field has 40% descriptive words and 10% directive words, while the other field has 60% directive words and 20% descriptive words, it is determined that the two fields have undergone a significant change in expression structure. At the same time, the coverage of keyword range is also counted. If the keywords in field A have only a 20% overlap in frequency in field B, it indicates that the field pair has changed at the keyword level, and the semantic change of the field pair is determined. The field pair is numbered and entered into the field semantic difference sequence as the input basis for subsequent structure judgment. For example, the fields "Preparations before connecting network devices" and "Operating steps" have a low match degree. The theme transitions from preparation to execution, and the keyword coverage is less than 30%. Therefore, they can be identified as field pairs with semantic differences.

[0070] S102: Based on the semantic difference sequence of fields, determine the functional definition items and business process markers of each field, analyze the continuous changes between functional classification numbers, compare the sequential connection status of business process markers, identify the field sequence numbers where the functional classifications are different and the connection of process markers is interrupted, and obtain the node boundary marker group.

[0071] The functional definitions in each field are analyzed one by one. Specifically, the functional section to which the field belongs in the manual is checked, such as whether it belongs to operation instructions, parameter definitions, configuration guidance, etc. A category number is assigned to each field using a manually set functional category sequence table. Simultaneously, the sequence label of the process segment is determined. This label comes from the process annotation items in the manual structure, such as the label sequence "Prepare," "Execute," "Verify," etc. The functional number and process sequence label are extracted from two adjacent fields, and the number values ​​are compared. If the functional definitions of the two fields come from different functional categories and the number values ​​differ significantly (e.g., between number 3 and number 7), it indicates a large functional transition. The process sequence labels of the two fields are then compared to determine the relationship between the process sequence label of the first field and the second field. If the process sequence label of the next field is not a continuous process item, such as the previous field belonging to the "Preparation" stage and the next field directly jumping to the "Parameter Configuration" stage instead of the "Operation" stage, then the process is considered to have broken. Further, the field numbers of all difference field pairs that exhibit this phenomenon are counted, and these field numbers are recorded as node boundary marker groups. In addition, after analyzing the total number of fields in the paragraph where the field is located, the common occurrence ratio of functional span and process breakage is counted to see if it reaches the set density. For example, if the functional number span of two fields is 4, the process sequence jumps 2 positions, and the current paragraph contains only 8 fields, then the difference density is 1.0, which exceeds the set density judgment standard of 0.6. At this time, the field number is recorded as a boundary node, and the resulting set of boundary node numbers serves as the basis for subsequent structural hierarchy judgment.

[0072] S103: Based on the node boundary identifier group, compare the semantic structure classification label and the structural hierarchy label, analyze the classification encoding span and hierarchy label jump of the fields before and after the node, determine the nodes where the classification attribute and hierarchy label change simultaneously, and obtain the structural breakpoint mapping set.

[0073] Extract the field number corresponding to each boundary node from the node boundary identifier group of the previous stage. Then, read the semantic structure classification tags attached to this field and its adjacent fields, such as tags like "description content", "execution content", "parameter description", etc., and extract the structural level label to which it belongs in the manual. This level label comes from the chapter numbering structure of the manual and is represented by numbers according to the hierarchical division in the actual manual. For example, "Chapter 1" is the first level, "1.1" is the second level, etc. After extracting the level number of the current and next fields, directly compare whether there is a jump between the two level values, that is, determine whether there is a direct jump from one level to another. If there is a jump behavior with a span greater than or equal to 1, it indicates that the structural hierarchy has changed. At the same time, continue to compare the classification tags of the two fields. Yes, if the difference in the category tag numbers of the two fields is greater than or equal to 2, it indicates that the semantic category has also changed significantly. When both of the above conditions are met, the field pair is confirmed as a structural breakpoint field pair. When recording the information of the breakpoint field, the field number, the difference in the category tag numbers of the two fields, the difference in the structural level tag numbers, and the physical line number or paragraph number of the field in the document should be recorded together as a part of the structural breakpoint mapping set. For example, if the category tag of field A is "description content", the tag number is 3, and the structural level is 1.0, and the category tag of field B is "parameter definition", the tag number is 5, and the structural level is 2.0, then the difference in category is 2, and the difference in level is 1, which meets the breakpoint judgment conditions. Field A and field B are recorded as a structural breakpoint mapping data and included in the structural breakpoint mapping set.

[0074] like Figure 3 As shown, the specific steps for obtaining path sequence association indicators are as follows:

[0075] S201: Based on the structural breakpoint mapping set, analyze the classification and coding of each structural segmentation node and field, compare the category distribution of the corresponding fields in the paragraph structure, determine the mapping changes of fields in the semantic classification of paragraph titles, descriptive statements and operation instructions, identify fields with different distributions in the mapping relationship, and obtain the paragraph jump sequence feature set.

[0076] The process involves extracting the field ID and paragraph position corresponding to each node, establishing a mapping table by matching field IDs with paragraph IDs, and then categorizing each field by its original structure. This code reflects the semantic type of the field; for example, paragraph titles are categorized as type 1, descriptive statements as type 2, and instruction fields as type 3. All fields are then aggregated by paragraph ID, and the distribution of field types in the aggregation results is statistically analyzed. The percentage of each type of field in each paragraph is calculated. For example, if a paragraph contains one title field, two description fields, and three instruction fields, the paragraph's structure distribution is: title 16.6%, description 33.3%, and instruction 50%. The proportion of this node's field in the current paragraph's structure distribution is then compared with that of other paragraphs. To determine whether there are differences in the distribution of similar fields, the difference in the proportion of a field's type between the current paragraph and a reference paragraph is calculated, and a threshold is set to judge the level of difference. The threshold is set to 20%, meaning that when the proportion of a field of a certain type in a paragraph deviates by more than 20% compared to other paragraphs, it is considered that there is a significant distribution difference. It is also determined whether the classification of the field changes in different paragraph structures. For example, if a field that was originally a title type appears as an instruction type field in other paragraphs, its semantic classification mapping relationship is marked as shifted. The shifted field is then identified and numbered, and all fields with abrupt changes in mapping relationship are grouped into a set. At the same time, the corresponding paragraph number, the type of field type change, and the relative position in the paragraph are recorded to form a paragraph jump sequence feature set. This feature set is used as a structural mapping reference for subsequent path aggregation.

[0077] S202: Based on the paragraph jump sequence feature set, aggregate user field jump paths, calculate the access frequency of fields in each path, analyze the behavior changes of fields during paragraph jumps, identify the field numbers with high-frequency access and clustered behavior, and obtain the node access spectrum set.

[0078] This analysis examines user field navigation behavior during the actual use of the interactive manual, extracting click paths and browsing history from the document reading, searching, and navigation processes. A field access path sequence is established for each user, with each navigation field recorded in the access path array according to the order of access. All user path data is then aggregated by field number, and the frequency of each field number is counted to represent its overall access frequency. Access frequency is divided into three levels: 0-10 times (low frequency), 11-50 times (medium frequency), and over 50 times (high frequency). The frequency level of each field is determined, and the contextual behavior of field access within each path is further analyzed, recording the changes in the field's position within the access path. If a field frequently appears as a path entry point... If a point or intermediate jump point is identified, it is further marked as a behavior clustering field. When statistically analyzing behavior changes, behavioral characteristics are identified by judging whether the same field appears repeatedly in different paths and whether it frequently forms jump combinations with adjacent fields. The behavior clustering reference value is set as the range of variation of the average occurrence position of the field in the path. If the value is less than 3, it means that the field occurrence position is relatively fixed and belongs to the behavior stable clustering field. Field numbers that meet the above conditions are uniformly included in the node access spectrum set, and the field numbers in the set are labeled with their access frequency, behavior stability and the paragraph path to which they belong, for reference in subsequent path sequence structure optimization. For example, field number 27 appears 63 times in 100 paths, with an average occurrence position of the 2nd or 3rd position of the path and a fluctuation range of 2. Because its frequency is high and its behavior is stable, it is included in the access spectrum set.

[0079] S203: Based on the node access spectrum set, analyze the access order of adjacent nodes in the jump path, optimize the arrangement of nodes that are repeated or have different combinations in the jump order, and obtain the path sequence association index by combining the combination relationship between nodes and the structural adjustment action.

[0080] The access order analysis is performed on adjacent nodes in the jump path of a field. For each field number in the path, a node pair combination sequence is constructed according to the jump order, and the frequency of each node pair combination is counted. Node pairs that appear more than 5 times are marked as common combinations. The occurrence of the same node in different positions in the path is judged. If a node number appears multiple times in different positions at the beginning and end of the path and the combination is different, its access order is rearranged, and it is moved closer to adjacent nodes with higher access frequency. Duplicate nodes are merged into one node, and the path order is regenerated. It is judged whether there are back jumps or redundant paths in the jump order. For example, if field number 12 jumps to number 24 and then jumps again. Returning to number 12 indicates a backtracking path. Such paths will have their backtracking segments removed, while valid forward combinations will be retained. Then, a combination structure will be generated based on the node access order. All commonly used node pairs will be extracted and sorted by their frequency of occurrence. Further, during the sorting process, it will be determined whether there are any changes in the combination relationship structure. For example, if a node pair changes from "number 3 → number 5" to "number 3 → number 8 → number 5", it will be marked as a change in the combination structure. In the structural adjustment action, the newly added path node number 8 will be added to the original path structure, and the path order will be updated to 3 → 8 → 5, completing the structural reconstruction of the path. All node combination information that has undergone order adjustment, combination change, and structural reconstruction in all paths will be compiled to generate path sequence association indicators.

[0081] like Figure 4 As shown, the specific steps for obtaining the path priority identification set are as follows:

[0082] S301: Based on the path sequence association index, compare the start order and end node of each path in the jump sequence, determine the arrangement characteristics of the path in the sorting structure, combine the number and order distribution of relay nodes in the path, optimize the path arrangement method, and obtain path stage distribution data.

[0083] For each path, extract the start and end point field numbers. Then, compare the position of these numbers in the entire path set to determine the overall arrangement of each path in the sorting structure. If the start node number is smaller and the end node number is larger in the path sequence, the path sorting direction is ascending; otherwise, it is descending. After sorting the path numbers in ascending order, extract the top 10% of paths as priority path segments. Count the number of relay nodes within each path, i.e., the total number of intermediate fields after excluding the start and end points. Record this number of relay nodes as the basic data for path complexity judgment. Then, read the arrangement order of each relay node in the path and compare it one by one with the order of similar nodes in other paths to determine if their relative order is consistent. If the order difference is within 1 position, then... If the order position fluctuates by more than 2 positions, it is marked as sequential convergence. At the same time, a threshold for the number of misalignments is set at 40% of the total number of relay nodes. If it exceeds this threshold, it is considered that there is a significant inconsistency in the path structure order. By analyzing the order arrangement of the start point, end point and relay nodes in each path, the structure is sorted according to three dimensions: path length, number of relay nodes and degree of arrangement difference. Paths with convergent arrangement structure are arranged first, and paths with serious order misalignment are placed last. Then, the arrangement index value of the path in the path set is readjusted according to the path order label to form the order distribution of the path after the structure arrangement of the start point, end point and relay nodes is unified. The start number, end number, number of relay nodes and structural consistency level of each path are combined to form the path stage distribution data.

[0084] S302: Based on the path stage distribution data, analyze the behavioral differences between frequently operated paths and other paths in terms of the number of jump behaviors, path structure, and node repetition, identify path numbers with concentrated access frequency and matching behavioral patterns, and obtain the path priority response set;

[0085] First, sort the paths by access frequency from highest to lowest, and extract the path numbers accessed more than 50 times as a high-frequency path set. Simultaneously, count the total number of jump actions for each path and compare it with the average number of actions. If the number of jumps for a single path is more than 20% higher than the average, it is recorded as a path with frequent jump actions. Next, count whether the path's field ID is accessed repeatedly. If the same ID appears twice or more in the same path, record the number of times it appears. Mark paths with a repetition rate exceeding 30% of their path length as repetitive paths. Then, compare the jump structure with the remaining low-frequency paths, setting the comparison indicators as: path length difference, structural node repetition rate difference, and jump count difference. Calculate the difference between high-frequency and low-frequency paths in these three aspects. If the three aspects differ... If all values ​​exceed the corresponding threshold, it is determined that there are behavioral pattern differences between the paths. Further filtering is performed to select path numbers that not only meet the high access frequency but also show concentrated performance in terms of jump structure and behavioral stability. The behavioral pattern matching conditions are set as follows: the path structure consistency rate is higher than 70% and the fluctuation range of the path node access order is less than 2 positions. Such path numbers are classified as behavioral pattern matching paths. The path numbers that meet the above conditions are packaged and combined with their behavioral feature values ​​to form a path priority response set. The recorded fields include: path number, access frequency, number of repeated nodes, number of jumps, structural stability level, etc. In the example, path number P047 has an access frequency of 88 times in the collected samples, 2 repeated nodes, a structural length of 6 segments, and a matching degree of 80%, and is included in the path priority response set.

[0086] S303: Based on the path priority response set, determine the grouping characteristics of the path number in the response sequence, analyze the consistency of the same group of paths in terms of jump direction, access density and operation order, aggregate the same type of paths according to the response category number, summarize the path combination members and response categories, and obtain the path priority identification set.

[0087] Read the position index of each path number in the full path response sequence, count the grouping identifier of the number in the response sequence, and compare whether the path numbers in the same group have adjacent or consecutive numbers in the sequence. If the maximum distance between path numbers is less than 3, it is marked as a response cluster path. Then, extract the jump direction value of all paths in the same group, that is, determine the direction sequence of field number increases or decreases. If most field numbers increase continuously in the path, the path jump direction is consistent and recorded as a positive sequence. If field numbers repeatedly increase or decrease, it is marked as a no-direction sequence. Then, count the access density of each path in the user operation data. The density is calculated by dividing the number of users accessing the path field by the total number of nodes in the path, and a density range is set. 0-0.2 is low density, 0.21-0.5 is medium density, and above 0.51 is high density. The operation order in each group of paths is compared to check whether the access order of fields in the path is consistent. If the first and last node numbers of most paths in the same group are the same or differ by 1 bit, the order consistency is determined to be strong. If the distribution of the first and last node numbers fluctuates by more than 3 bits, the order consistency is determined to be weak. Group by path number and set response category number, divided into 1 to 5 levels from low consistency to high consistency. Paths in the same group are uniformly classified into the same category number to form a path response category structure. The path combinations under the same category number are summarized into path combination members to obtain a list of all path members under each response category, and a path priority identification set is constructed.

[0088] like Figure 5 As shown, the specific steps for obtaining the field structure change parameters are as follows:

[0089] S401: Based on the path priority identification set, analyze the priority labels and path group members, determine the distribution status of the fields corresponding to each path in the manual structure hierarchy, compare the changes in field classification labels between the codes of each structure hierarchy, identify the fields whose classification labels have changed, and obtain the structure hierarchy change index.

[0090] Extract the field numbers and their hierarchical numbers contained in each path. Read the hierarchical information of each field within the manual document structure. This hierarchical information originates from the structural numbers of the chapter, subsection, and functional block to which the field belongs, increasing from top to bottom according to the hierarchical number structure. For example, the main title level is 1, the subsection is 1.1, the functional field is 1.1.1, and so on. Calculate the distribution range of field hierarchies covered by path group members under the same priority label. Record the start and end numbers corresponding to each path group at each level. Determine whether the fields are concentrated in a specific structural level within the path. For example, if a group of path fields are concentrated between level numbers 2.1 and 2.3, it is recorded as a concentrated distribution path group. Conversely, if the path fields span multiple chapter levels, such as extending from 1.1 to 3.2, it is marked as a cross-level path group. Next, extract the classification label for each field within the path. This label represents the semantic category of the field, such as "parameter definition," "parameter classification," etc. The system compares the categorization labels within the same path, such as "Notes" and "Steps / Operations," to see if there are any cross-category jumps. For example, if a field is labeled "Steps / Operations" and the next field is labeled "Notes," a label jump has occurred. The system then compares the categorization label with its corresponding structural level number. If the label changes from a lower level to a higher level or from a category to a non-adjacent category during the path progression, it is marked as a categorization label change field. These field numbers are extracted and formed into a change field set. The system records the path number, field number, original label, changed label, original structural level number, and changed level number, and combines them to generate a structural hierarchical change index. In the example, path P103 contains fields F021 and F033. F021 belongs to the "Steps / Operations" label and is at level 2.1.2, while F033 belongs to the "Notes" label and is at level 1.3. Since both the label and level have changed, field F033 is included in this index set.

[0091] S402: Based on the structural hierarchical change index, compare the classification label with the structural level code, determine the correspondence between the current classification and the existing structural level, analyze the structural distribution differences between the classification change field and other fields in the manual, identify the field number of the structural distribution change, and obtain the classification change related data.

[0092] The process involves calling the current category label of a field and its corresponding structural level number, comparing the current label with the level correspondence in the preset structural template, and determining whether the label's position within the structure is reasonable. For example, the "Notes" label should belong to a level 3 structure according to the template. If this label appears in a level 1 structure field, it is recorded as a level-abnormal field. The template standard is set as follows: title tags belong to level 1, description tags belong to level 2, and parameter and step tags belong to level 3. Based on this structure, the process determines whether the category and structural level correspond, and counts the inconsistent field numbers. Then, each changed field is selected as a reference point, and the structural level numbers and labels of adjacent fields within the same paragraph are read forward and backward. The category span and structural level span between this field and adjacent fields are calculated. If the category span exceeds two or more and the hierarchical span is two or more, the field is considered to have a structural distribution difference from surrounding fields. This difference field is recorded in the structural distribution change field set. Then, the number of such distribution difference fields is screened in the entire manual field structure. If a certain type of distribution difference field accounts for more than 10% of the total fields, it is additionally marked as a structurally unstable field. The field number of this part is combined with the corresponding category, hierarchical and other information and recorded as the affiliation change related data. In the example, field F087 was originally labeled "Explanation" and is now labeled "Parameter Definition". The structural hierarchical level has been adjusted from 2.2 to 3.4. The fields before and after are "Step Operation" and "Reference Explanation". The label span is 3 and the hierarchical span is 2, which meets the recording conditions. F087 is included in the affiliation change related data set.

[0093] S403: Based on the data related to changes in attribution, analyze the distribution and scope of influence of the changed fields in the manual's structural hierarchy, optimize the criteria for judging the scope of field influence, adjust the influence distribution parameters of the classification change fields, and obtain the field structure change parameters.

[0094] The criteria for determining the scope of influence of optimized fields are based on the following formula:

[0095] ;

[0096] Calculated field influence range correction parameter Adjusting the impact distribution parameters of the classification change fields yields the field structure change parameters, where... Representing the The amount of change in the hierarchical position of each field between the current version and previous versions. Representing the The percentage change in the hierarchical position of each field. This represents the average influence level among the path sequence correlation indicators. This represents the total number of fields involved in the calculation.

[0097] The field impact range correction parameter refers to a quantitative parameter used to measure the degree of change in the overall impact range of the classification change field on the manual structure during the manual structure adjustment process. This parameter is calculated by combining the changes in the hierarchical position and the proportion of hierarchical changes of each field, and referring to the average impact of path sequence related indicators.

[0098] First, identify the hierarchical number of each field in the historical and current structures, and denote them as follows: and The fields are numbered sequentially from 1 to 6, and the change in the hierarchical position of the fields is obtained by difference calculation, defined as follows: For example, if field 1 has a hierarchy level of 2 in the historical structure and a hierarchy level of 3 in the current structure, then... Applying this method sequentially to fields 2 through 6, the resulting changes are as follows: Field 2: Field 3: Field 4: Field 5: Field 6: Then, based on the maximum value normalization method, using the maximum level value of 5 in the current structure as the normalization denominator, the level number of the current structure for each field is determined. Normalization is performed to calculate the normalized hierarchical proportion. The normalization result is:

[0099] Field 1: ;

[0100] Field 2: ;

[0101] Field 3: ;

[0102] Field 4: ;

[0103] Field 5: ;

[0104] Field 6: .

[0105] Then and The formula for calculating the field's influence range correction parameter is as follows:

[0106] ;

[0107] The total number of fields The average influence level item in the path sequence correlation index Calculate step by step:

[0108] Field 1: ;

[0109] Field 2: ;

[0110] Field 3: ;

[0111] Field 4: ;

[0112] Field 5: ;

[0113] Field 6: ;

[0114] The sum of the difference terms is The average difference is calculated as follows: The path-affected item is The final calculation result is:

[0115] ;

[0116] Based on the preset structural impact judgment criteria, the field correction parameters are divided into three intervals:

[0117] when When the structure remains stable, the field classification does not need to be adjusted.

[0118] when If the structure is slightly fluctuating, the field may be selectively reconstructed.

[0119] when When the system is deemed to have undergone significant structural changes, it is necessary to perform field reclassification and re-division, and adjust the path structure accordingly. The current value... Located in the third interval, this indicates a significant difference in the magnitude of the change between field hierarchy and path operation.

[0120] like Figure 6 As shown, the specific steps for obtaining node chain encoding information are as follows:

[0121] S501: Based on the field structure change parameters, compare the hierarchical distribution and classification status of the fields involved in the manual structure, determine the changes of the fields between each structural node, identify the fields whose status has changed after the structural hierarchy adjustment or classification change, and obtain the hierarchical offset node group.

[0122] For each field, its original hierarchical number and current hierarchical number within the manual structure are read and compared. This process counts whether the field has undergone hierarchical shifts between structural nodes. If the original hierarchical number is 2.1 and the current hierarchical number is 3.1, it is considered a downward shift; if the current number changes to 1.2, it is considered an upward shift. Next, the original classification status and adjusted classification label of the field are extracted. For example, if the original was "Parameter Definition" and the adjusted label is "Step Description," the classification codes corresponding to the classification labels are compared to determine if the code values ​​have changed. If the difference in classification codes is greater than or equal to 2, it is considered a classification shift field. Finally, the hierarchical shift field and the classification shift field are intersected to identify fields where both the structural hierarchy and classification label have changed. These are then considered valid hierarchical shift fields. The field numbers are extracted and their hierarchical numbers and classification labels before and after the changes are recorded to construct a set of field offset information. Then, the fields in the set are grouped by paragraph number, and the number of offset fields within the same paragraph is counted. If the proportion of offset fields in the paragraph exceeds 25% of the total number of fields in the paragraph, the paragraph is marked as a structurally unstable paragraph. Furthermore, structural jump nodes are marked within the entire manual structure, that is, field numbers that jump directly from a lower structure to a higher structure, or vice versa. For example, if field F061 is adjusted from structure number 2.3 to 4.1, the classification label is changed from "description text" to "equipment configuration", the category number is adjusted from 06 to 10, the offset span is greater than 2 levels and the label span is 4, this field is identified as a structural hierarchical offset field and forms a hierarchical offset node group.

[0123] S502: Based on the hierarchical offset node group, determine the node trajectory of multi-user concurrent editing operations and reference chain structure fields, compare the frequency and position of content changes of nodes during editing and referencing, identify nodes with more changes, and obtain the node evolution trajectory group.

[0124] Read all operation logs in the multi-user editing records, aggregate the operation user identifier, editing timestamp, field number, and summary of content before and after editing recorded in each log, categorize all editing events according to field number, and then count the number of times each field appears in all editing records to determine if concurrent editing exists. The concurrency judgment condition is set as: different users perform editing operations on the same field within the same hour. If this condition is met, the field is marked as a concurrent editing node. At the same time, extract the relationship chain of the field referenced by other fields and analyze its reference link path in the manual structure. For example, if field F035 is referenced three times by fields F041, F052, and F067, then its reference chain depth is recorded as 3. Form a trajectory sequence with the reference field number and the reference position of the corresponding field, and then count whether the content of the field changes before and after each reference. If the content changes after the reference, the reference is considered as a concurrency node. If there are changes in key statements, keywords, or parameter segments before use, the reference is identified as an influential reference. The number of influential references for a field in all references is accumulated. If it exceeds 60% of the total number of references, the field is marked as a change-sensitive node. The change position of each field in the editing trajectory is then counted, that is, the position number segment in the field content structure where the editing occurred. For example, if the field content consists of three segments, and the main editing is concentrated in the first and third segments, the recorded position range is 1 and 3. Field numbers with an editing frequency of more than 5 times and a reference change rate of more than 60% are extracted. Together with the number of editing users, the depth of the reference chain, and the sequence of change segments, they form a node evolution trajectory group. In the example, field F105 was edited 7 times by 4 users, 3 of which were operations within 1 hour. The number of referenced fields was 4. The content before and after the 3 references was different. The reference influence rate was 75%. This field was classified into the node evolution trajectory group.

[0125] S503: Based on the node evolution trajectory group, combined with the operator's identity and time point, adjust the differentiation criteria of the node chain structure, analyze the editing order and differentiation path of each node in the link, optimize the indexing method according to the relationship between the node trajectory and the link, and obtain the node chain encoding information;

[0126] Based on the field numbers, editing times, user identifiers, and change frequencies recorded in the node evolution trajectory group, an operation sequence record table is formed for each field. Each editing action for that field is arranged in ascending chronological order, and the editor's identity is marked. The first and last users are extracted as the endpoints of the trajectory. It is determined whether multiple users continuously modify the data. If the number of participating users exceeds 3 and the operation time span exceeds 48 hours, the field is marked as a deep evolution node. The sequence of changed segments and paragraph positions in each editing process is extracted. It is determined whether two adjacent edits involve the same content segment. If two consecutive edits involve different segments, a path differentiation event is recorded. The differentiation paths of all fields are summarized into a field path graph, and the occurrence of divergences in the path is statistically analyzed. The number and location of nodes in the branch are determined, and the link structure between the field and its referenced fields is read. If the referenced field is modified earlier than the modified field and is referenced again after modification, it is marked as a link backtracking structure node. All such nodes are re-indexed, and the original chain structure built according to the field number order is adjusted to a three-axis structure based on time + user + rank. The index numbering rules are rebuilt, and the new numbering encoding rule is set as: field number + editor number + editing time sequence number. For example, if field F058 is operated by user U004 in the fifth edit, its new index number is F058_U004_05. The node chain encoding information is constructed, and all nodes are arranged according to the link graph sequence to form a traceable index path set.

[0127] like Figure 7 As shown, an interactive manual data management system includes:

[0128] The structure segmentation module identifies the direction of attribute changes between fields based on semantic tag content, compares the relationship between adjacent fields, judges semantic structure changes, determines structure segmentation nodes, and obtains a set of structure breakpoint mappings.

[0129] The path aggregation module, based on the structural breakpoint mapping set, determines the application scenario of the manual data structure, analyzes the user's operation sequence in paragraph structure fields and jump chains, aggregates operation trajectories, identifies high-frequency nodes, and obtains path sequence association indicators.

[0130] The priority path module analyzes the positional characteristics of paths in the sequence based on path sequence association indicators, compares the differences in behavioral patterns between high-frequency paths and other paths, determines the priority response path, and summarizes the priority response path members to obtain the path priority identification set.

[0131] The structural change module analyzes the distribution of related fields in the manual structure based on the path priority identification set, compares the current field with the historical structural hierarchy changes, determines whether the structural classification has been adjusted, identifies the fields that have undergone classification changes, and obtains the field structure change parameters.

[0132] The node tracking module analyzes the node trajectories of fields edited concurrently by multiple users and reference chain structure fields based on field structure change parameters, identifies frequently changing nodes, and adjusts the chain index by combining identity and time point to obtain node chain encoding information.

[0133] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An interactive manual data management method, characterized in that, The method includes: S1: Based on semantic tag content, identify the direction of attribute change between fields, compare the relationship between adjacent fields, determine semantic structure changes, determine structural segmentation nodes, and obtain a set of structural breakpoint mappings; S2: Based on the structure breakpoint mapping set, determine the application scenario of the manual data structure, analyze the user's operation sequence in paragraph structure fields and jump chains, aggregate operation trajectories, identify high-frequency nodes, and obtain path sequence association indicators. S3: Based on the path sequence association index, analyze the positional characteristics of the path in the sequence, compare the differences in behavior patterns between high-frequency paths and other paths, determine the priority response path, and summarize the priority response path members to obtain the path priority identification set. S4: Based on the path priority identification set, analyze the distribution of related fields in the manual structure, compare the current field with the historical structure hierarchy changes, determine whether the structure classification has been adjusted, identify the fields that have undergone classification changes, and obtain the field structure change parameters. S5: Based on the field structure change parameters, analyze the node trajectory of the multi-user concurrent editing field and the reference chain structure field, identify frequently changing nodes, and adjust the chain index in combination with identity and time point to obtain node chain encoding information; The specific steps for obtaining the path sequence association index are as follows: S201: Based on the structure breakpoint mapping set, analyze the classification codes of each structure segmentation node and field, compare the category distribution of the corresponding fields in the paragraph structure, determine the mapping changes of the fields in the semantic classification of paragraph titles, descriptions and operation instructions, identify the fields with different distributions in the mapping relationship, and obtain the paragraph jump sequence feature set. S202: Based on the paragraph jump sequence feature set, aggregate user field jump paths, calculate the access frequency of fields in each path, analyze the behavior changes of fields during paragraph jumps, identify the field numbers with high-frequency access and clustered behavior, and obtain the node access spectrum set. S203: Based on the node access spectrum set, analyze the access order of adjacent nodes in the jump path, optimize the arrangement of nodes that are repeated or have changes in combination in the jump order, and obtain the path sequence association index by combining the combination relationship between nodes and the structural adjustment action. The specific steps for obtaining the path priority identification set are as follows: S301: Based on the path sequence association index, compare the start order and end node of each path in the jump sequence, determine the arrangement characteristics of the path in the sorting structure, and optimize the path arrangement by combining the number and order distribution of relay nodes in the path to obtain path stage distribution data. S302: Based on the path stage distribution data, analyze the behavioral differences between frequently operated paths and other paths in terms of the number of jump behaviors, path structure, and node repetition phenomena, identify path numbers with concentrated access frequency and matching behavior patterns, and obtain the path priority response set; S303: Based on the path priority response set, determine the grouping characteristics of the path number in the response sequence, analyze the consistency of the same group of paths in terms of jump direction, access density and operation order, aggregate the same type of paths according to the response category number, summarize the path combination members and response categories, and obtain the path priority identification set.

2. The interactive manual data management method according to claim 1, characterized in that, The structural breakpoint mapping set includes segmentation interval number, node positioning attribute, and structural classification code; the path sequence association index includes node sequence identifier, path aggregation attribute, and behavior pattern code; the path priority identification set includes priority label, path group member, and response category number; the field structure change parameter includes hierarchical adjustment item, classification change item, and impact degree item; and the node chain encoding information includes node number, link sequence, and edit information index.

3. The interactive manual data management method according to claim 1, characterized in that, The specific steps for obtaining the structural breakpoint mapping set are as follows: S101: Based on semantic tag content, compare the keyword matching degree of adjacent fields and the direction of topic category change, determine the changes in semantic expression and classification attributes of field pairs, identify field pairs that have changed in semantic description and keyword coverage, and obtain the field semantic difference sequence. S102: Based on the semantic difference sequence of the fields, determine the functional definition items and business process markers of each field, analyze the continuous changes between functional classification numbers, compare the sequential connection status of business process markers, identify the field sequence numbers where the functional classifications are different and the connection of process markers is interrupted, and obtain the node boundary marker group. S103: Based on the node boundary identifier group, compare the semantic structure classification label and the structural hierarchy label, analyze the classification encoding span and hierarchy label jump of the fields before and after the node, determine the nodes where the classification attribute and hierarchy label change simultaneously, and obtain the structural breakpoint mapping set.

4. The interactive manual data management method according to claim 1, characterized in that, The specific steps for obtaining the field structure change parameters are as follows: S401: Based on the path priority identification set, analyze the priority labels and path group members, determine the distribution status of the fields corresponding to each path in the manual structure hierarchy, compare the changes in the field classification labels between the codes of each structure hierarchy, identify the fields whose classification labels have changed, and obtain the structure hierarchy change index. S402: Based on the structural hierarchical change index, compare the classification label with the structural level code, determine the correspondence between the current classification and the existing structural level, analyze the structural distribution differences between the classification change field and other fields in the manual, identify the field number of the structural distribution change, and obtain the classification change related data. S403: Based on the aforementioned attribution change association data, analyze the distribution and impact range of the change fields in the manual's structural hierarchy, optimize the criteria for determining the field's impact range, adjust the impact distribution parameters of the classification change fields, and obtain the field structure change parameters.

5. The interactive manual data management method according to claim 1, characterized in that, The specific steps for obtaining the node chain encoding information are as follows: S501: Based on the field structure change parameters, compare the hierarchical distribution and classification status of the fields involved in the manual structure, determine the changes of the fields between each structural node, identify the fields whose status has changed after the structural hierarchy adjustment or classification change, and obtain the hierarchical offset node group. S502: Based on the hierarchical offset node group, determine the node trajectory of multi-user concurrent editing operations and reference chain structure fields, compare the frequency and position of content changes of nodes during editing and referencing, identify nodes with more changes, and obtain the node evolution trajectory group. S503: Based on the node evolution trajectory group, combined with the operator's identity and time point, adjust the differentiation criteria of the node chain structure, analyze the editing order and differentiation path of each node in the link, optimize the indexing method according to the relationship between the node trajectory and the link, and obtain the node chain encoding information.

6. The interactive manual data management method according to claim 1, characterized in that, The semantic tag content refers to the semantic description, keywords and classification tags carried by each field in the manual, and the attribute change direction refers to the trend and direction of the semantic content change between two adjacent fields.

7. The interactive manual data management method according to claim 1, characterized in that, The manual's data structure refers to the ordered relationship and data hierarchy among all fields, paragraphs, and nodes in the manual, while the application scenario refers to the user's business process, role requirements, or purpose of use when using the manual.

8. An interactive manual data management system, the system being used to implement the interactive manual data management method as described in any one of claims 1-7, characterized in that, The system includes: The structure segmentation module identifies the direction of attribute changes between fields based on semantic tag content, compares the relationship between adjacent fields, judges semantic structure changes, determines structure segmentation nodes, and obtains a set of structure breakpoint mappings. Based on the structure breakpoint mapping set, the path aggregation module determines the application scenario of the manual data structure, analyzes the user's operation sequence in paragraph structure fields and jump chains, aggregates operation trajectories, identifies high-frequency nodes, and obtains path sequence association indicators. Based on the path sequence association index, the priority path module analyzes the positional characteristics of the path in the sequence, compares the differences in behavior patterns between high-frequency paths and other paths, determines the priority response path, and summarizes the priority response path members to obtain the path priority identification set. The structure change module analyzes the distribution of associated fields in the manual structure based on the path priority identification set, compares the current field with the historical structure hierarchy changes, determines whether the structure classification has been adjusted, identifies fields that have undergone classification changes, and obtains field structure change parameters. The node tracking module analyzes the node trajectories of fields edited concurrently by multiple users and reference chain structure fields based on the field structure change parameters, identifies frequently changing nodes, and adjusts the chain index in combination with identity and time point to obtain node chain encoding information.

Images