Digital-based print information dynamic flow management method and system

Abstract

The application provides a digital-based printing information dynamic process management method and system, and relates to the technical field of data processing.The method comprises the following steps: dividing a process data chain into input nodes, conversion nodes and output nodes, expanding along the predecessor path and successor path of the target node of the change instruction, establishing the connection level between each type of node and the target node, connecting and reconstructing the type nodes of different connection levels respectively, identifying the sequence offset degree after process recombination, obtaining the process displacement, identifying the path intersection situation generated in the recombination process, and splitting the path of the type node with multiple predecessors or successors, identifying the modification degree of the connection relationship of each type of node, obtaining the connection reconstruction amount, selecting the path meeting the preset combination condition as the target process data chain, and generating the process execution sequence.The application can realize the dynamic reconstruction and synchronous update of the printing process under the condition of business change.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method and system for dynamic process management of printing information based on digitalization. Background Technology

[0002] In existing technologies, printing information flow management typically involves a business management platform to uniformly collect, store, and process printing orders, layout files, process parameters, machine status, and process progress. In practice, the system receives customer orders and printing files, generates electronic work orders based on preset business rules, and associates information such as paper type, color requirements, post-printing processes, and delivery time with the corresponding process nodes. Then, through a database and process control module, the relevant data is distributed to stages such as plate making, printing, lamination, die cutting, and binding to achieve digital management and process collaboration of the printing business process.

[0003] However, existing technologies typically determine the process nodes and workflow relationships once a pre-set template is established when an order is created. Subsequent processes mainly rely on the initial settings to continue execution. This may not be able to automatically reconstruct subsequent processes in response to business changes during order execution. For example, after a packaging and printing order has completed document review and entered the printing scheduling stage, the customer may temporarily request to change the process from direct die-cutting after printing to adding lamination before die-cutting after printing. Existing systems may only be able to modify order notes or local parameters, and cannot synchronously adjust the relationships of subsequent processes that have already been issued, resulting in the process status in the system remaining at the original path. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for dynamic process management of printing information based on digitalization, in order to solve the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: Firstly, a digital-based dynamic workflow management method for printing information, the method comprising: The process data chain for obtaining printing orders; By dividing the process data chain into input nodes, transformation nodes, and output nodes, and extracting the predecessor and successor paths of each type of node to establish path participation identifiers, node process data is obtained. Based on the node process data, the connection hierarchy between each type of node and the target node is established by extending along the predecessor and successor paths of the target node of the change instruction to obtain the impact diffusion data. Based on the impact diffusion data, connections and reconstructions are performed for nodes of different connection levels, and the path participation identifiers of each type of node are updated synchronously to obtain hierarchical reorganization data. Based on the hierarchical reorganization data, calculate the difference in the sequential number of each type of node in the process data chain and the hierarchical reorganization data, identify the degree of sequential offset after process reorganization, and obtain the process displacement. Based on the hierarchical reorganization data, identify the path intersections that occur during the reorganization process, and split the path of type nodes with multiple predecessors or multiple successors to obtain the resolution process data. Based on the resolution process data, the number of new connections and disconnections for each type of node in the resolution process are counted, the degree of modification of the connection relationship of each type of node is identified, and the connection reconstruction amount is obtained. Based on the process displacement and connection reconstruction amount, the path in the decomposition process data that meets the preset combination conditions is selected as the target process data chain, and the process execution sequence is generated.

[0006] Furthermore, based on the node process data, the process extends along the predecessor and successor paths of the target node of the change instruction to establish a connection hierarchy between various types of nodes and the target node, thereby obtaining impact diffusion data, including: Based on the node process data, identify the target node identifier in the change instruction, and extract the path participation identifier and path number of the target node to obtain the target node location data; Based on the target node location data, trace back adjacent nodes segment by segment along the predecessor path of the target node, and record the number of path segments traversed between the current node and the target node to obtain the predecessor extension data. Based on the target node location data, traverse adjacent nodes segment by segment along the successor path of the target node, and record the number of path segments traversed between the current node and the target node to obtain the successor extended data. Based on the predecessor and successor expansion data, the number of path segments is used as the connection level between each node and the target node. The node category identifier and path participation identifier are recorded to obtain the node level data. Based on the node hierarchy data, the node category identifier, path participation identifier, and connection level are combined and arranged in order of path number to obtain the impact diffusion data.

[0007] Furthermore, based on the impact diffusion data, connections and reconstructions are performed separately for nodes of different connection levels, and the path participation identifiers of each type of node are updated synchronously to obtain hierarchical reorganization data, including: Based on the impact diffusion data, nodes with connection levels within the preset level range are classified as recombination nodes, and nodes with connection levels outside the preset level range are classified as maintenance nodes, thus obtaining node grouping data; Based on the node grouping data, the original predecessor connection records and the original successor connection records of the recombined nodes are removed one by one, and the connection positions after removal are marked to obtain the broken link position data. Based on the broken link location data, the reconstructed nodes are inserted sequentially into the broken link locations, and the predecessor and successor connections are re-established to obtain the reconstructed connection data. Based on the reconstructed connection data, the nodes are reconnected to the reconstructed connection data in the order they are in the process data chain, resulting in reconstructed connection structure data. Based on the recombined connection structure data, the predecessor path record and successor path record of the node whose connection has changed are extracted again, and the path participation identifier is updated to obtain hierarchical recombined data.

[0008] Furthermore, based on the hierarchical reorganization data, the difference in the sequential numbering of each type of node in the process data chain and the hierarchical reorganization data is calculated to identify the degree of sequential offset after process reorganization, and the process displacement is obtained, including: Based on the hierarchical reorganization data, the difference between the reorganization sequence numbers of each type of node is calculated to identify the degree of change in the execution order of each type of node before and after the process reorganization, and the sequence offset item is obtained. Based on the hierarchical reorganization data, the degree of linkage impact of each type of node on the cross-path structure when the order changes is calculated, and the span correlation term is obtained. Based on the hierarchical reorganization data, the difference between the path numbers of each type of node before and after reorganization is calculated, the degree of change in path affiliation of each type of node is identified, and the path migration item is obtained. By fusing sequence offset, span association, and path migration items, the overall offset of each type of node in terms of execution order, cross-path association, and path affiliation is identified, and the process displacement is obtained.

[0009] Furthermore, based on the hierarchical reorganization data, path intersections generated during the reorganization process are identified, and path splitting is performed on nodes with multiple predecessors or successors to obtain resolution process data, including: Based on the hierarchical reorganization data, nodes with multiple predecessor or successor connection records are selected and marked as intersection nodes. At the same time, the connection combination relationship is recorded to obtain the path intersection node data. Based on the path intersection node data, each predecessor connection record and each successor connection record are paired into independent connection relationships to obtain connection combination data; Based on the connection combination data, the cross nodes are replaced with multiple independent nodes, and an identifier is assigned to each independent node. The node category identifier and path participation identifier of the cross nodes are inherited to obtain the node splitting data. Based on the node-splitting data, the independent nodes are re-embedded into the hierarchical reorganization data according to the connection and combination relationship to obtain the resolution process data.

[0010] Furthermore, based on the resolution process data, the number of new connections and disconnections for each type of node during the resolution process is statistically analyzed to identify the degree of modification of the connection relationships for each type of node, thus obtaining the connection reconstruction quantity, including: Based on the resolution process data, the number of new connections and disconnections for each type of node in the resolution process are counted, the basic degree of connection modification for each type of node in the resolution process is identified, and the connection rewriting items are obtained. Based on the resolution process data, the degree of deviation between connection increase and connection termination during the connection reconstruction process of each type of node is calculated to obtain the connection imbalance term. Based on the resolution process data, the degree of expansion of the connection structure caused by the combined effects of path splitting and path participation changes of each type of node is calculated to obtain the path expansion term. By fusing connection rewriting, connection imbalance, and path expansion items, the comprehensive reconstruction degree of each type of node in terms of connection rewriting, connection imbalance, and path impact is identified, and the connection reconstruction quantity is obtained.

[0011] Furthermore, based on the process displacement and connection reconstruction amount, the path in the decompiled process data that satisfies the preset combination conditions is selected as the target process data chain, generating a process execution sequence, including: Based on the digestion process data, the node connection relationships in each path are extracted and divided according to the path number. The node set and connection structure of each path are recorded to obtain the path structure data. Based on the path structure data, the process displacement and connection reconstruction amount in each path are weighted and fused to calculate the fused path value and obtain the path numerical mapping data. Based on the path numerical mapping data, the fused path value of each path is compared with the preset combination conditions, and the paths that meet the preset combination conditions are selected to obtain candidate path data. Based on the candidate path data, the parts of the path containing duplicate nodes or conflicting connections are removed, and the node sequences with continuous connections are retained to obtain the target path data; Based on the target path data, each node is expanded sequentially according to its predecessor and successor connections, and then sorted by path number to generate a process execution sequence.

[0012] Secondly, a digital printing information dynamic process management system, the system comprising: The data module is used to obtain the process data chain of printing orders; The node module is used to divide the process data chain into input nodes, transformation nodes, and output nodes, and extract the predecessor and successor paths of each type of node to establish path participation identifiers, thereby obtaining node process data. The connection module is used to expand along the predecessor and successor paths of the target node of the change instruction based on the node process data, establish the connection hierarchy between various types of nodes and the target node, and obtain the impact diffusion data. The reorganization module is used to connect and rebuild nodes of different connection levels according to the impact diffusion data, and to update the path participation identifiers of each type of node simultaneously to obtain hierarchical reorganization data. The displacement module is used to calculate the difference in the sequential number of each type of node in the process data chain and the hierarchical reorganization data based on the hierarchical reorganization data, identify the degree of sequential offset after process reorganization, and obtain the process displacement amount. The splitting module is used to identify path intersections during the reorganization process based on the hierarchical reorganization data, and to split the paths of type nodes with multiple predecessors or multiple successors to obtain the resolution process data. The reconstruction module is used to count the number of new connections and disconnections of each type of node in the resolution process based on the resolution process data, identify the degree of modification of the connection relationship of each type of node, and obtain the connection reconstruction quantity. The process module is used to select the path in the decomposition process data that meets the preset combination conditions as the target process data chain based on the process displacement and connection reconstruction amount, and generate the process execution sequence.

[0013] The above-described solution of the present invention has at least the following beneficial effects: This invention establishes a connection hierarchy between node process data and target nodes. Then, based on the impact diffusion data, it connects and reconstructs nodes of different connection levels. This optimizes process change processing from a complete chain rewriting to a hierarchical, bounded, and controllable reorganization method. If the entire process is regenerated for each change, not only is the computational cost high, but it is also prone to unnecessary conflicts with historical data, status data, and scheduling data of the unchanged parts. By performing hierarchical reorganization through connection levels, the system can distinguish the truly affected nodes from the relatively stable nodes in terms of data. While ensuring process connectivity, it reduces the degree of disturbance to the global data structure, reduces the duplication of processing of irrelevant nodes, improves the computational efficiency of process reconstruction, and ensures that the nodes after local reorganization can still be embedded in the original process chain, maintaining the overall continuity and integrity of process data.

[0014] This invention identifies the degree of sequence shift after process reorganization by calculating the difference in the sequence numbers of various types of nodes in the process data chain and hierarchical reorganization data. It can quantify the magnitude of the changes and the extent of the change in node sequence. For digital process management, quantitative description is the basis for the system to make subsequent judgments, such as whether the change is a local fine-tuning, whether production scheduling needs to be retried, or whether certain process notifications need to be reissued. By calculating the difference in sequence numbers, the system can transform the originally abstract process sequence changes into comparable, sortable, and threshold-judgmentable numerical objects, significantly enhancing the data analysis capabilities of process management. It gives the process reorganization results evaluable attributes, enabling the system not only to rebuild the process but also to understand the strength of the impact of the reconstruction on the execution sequence, supporting more refined process control and change response strategies.

[0015] This invention identifies path intersections during the reorganization process and splits paths for nodes with multiple predecessors or successors. When complex connections arise due to process changes, the system can proactively identify potentially ambiguous intersections and break down the originally coupled multiple connections into more clearly defined process units through data splitting. If a node simultaneously receives multiple preceding sources or branches to multiple subsequent directions, and this relationship is temporarily formed during dynamic changes, then if the system retains this intersection structure indiscriminately, problems such as unclear path attribution, ambiguous process responsibility boundaries, and state synchronization conflicts may easily occur during subsequent execution, monitoring, statistics, and tracking. By obtaining process data through path splitting, the data dependencies of each path become more singular and clear, reducing ambiguous structures in the process chain, improving the standardization of flowchart data, effectively enhancing the interpretability and executability of process data after dynamic reorganization, and avoiding pseudo-connected structures that exist logically but are chaotic in execution within the system.

[0016] This invention identifies the degree of modification to the connection relationships of various node types by statistically analyzing the number of new and broken connections during the resolution process, thus obtaining the connection reconstruction quantity. The system can measure the extent of process reorganization from the structural level of connection relationship changes. In process management, the direction of business flow is determined not only by the node order but also by the connection relationships between nodes. Even if a node's position changes slightly, its actual process role and dependencies may be completely different if its upstream or downstream connected objects change. By statistically analyzing new and broken connections and extracting this structural change to form the connection reconstruction quantity, the system can determine whether a change is a simple sequence adjustment or a deep modification involving a reshaping of the business flow. This enables the system to simultaneously perceive both positional and relational changes, providing a dual-dimensional characterization of process reorganization. The connection reconstruction quantity reflects the impact of changes on the process network, helping to improve the accuracy of subsequent system decisions, scheduling synchronization, and execution control.

[0017] This invention further filters and constrains candidate paths through two types of quantitative indicators, selecting more reasonable, stable, and business-oriented execution paths. After dynamic reconstruction, there may be multiple seemingly connectable paths, but not every path is suitable for actual execution. By comprehensively considering the degree of sequence offset and the degree of change in connection relationships, the system can filter out paths with excessive disturbance, high risk of logical conflict, or insufficient continuity, retaining a better target process data chain, improving the certainty of the final execution sequence, reducing manual review and intervention, and making the output results have clear numerical basis. Based on structured analysis and indicator screening, the process execution sequence is more suitable for direct use in driving subsequent processes, state transitions, and execution control, significantly enhancing the automation level and reliability of digital printing process management. Attached Figure Description

[0018] Figure 1 This is a flowchart of a digital-based dynamic process management method for printing information provided in an embodiment of the present invention. Detailed Implementation

[0019] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0020] like Figure 1 As shown, embodiments of the present invention propose a digital-based dynamic workflow management method for printing information, the method comprising: The process data chain for obtaining printing orders; By dividing the process data chain into input nodes, transformation nodes, and output nodes, and extracting the predecessor and successor paths of each type of node to establish path participation identifiers, node process data is obtained. Based on the node process data, the connection hierarchy between each type of node and the target node is established by extending along the predecessor and successor paths of the target node of the change instruction to obtain the impact diffusion data. Based on the impact diffusion data, connections and reconstructions are performed for nodes of different connection levels, and the path participation identifiers of each type of node are updated synchronously to obtain hierarchical reorganization data. Based on the hierarchical reorganization data, calculate the difference in the sequential number of each type of node in the process data chain and the hierarchical reorganization data, identify the degree of sequential offset after process reorganization, and obtain the process displacement. Based on the hierarchical reorganization data, identify the path intersections that occur during the reorganization process, and split the path of type nodes with multiple predecessors or multiple successors to obtain the resolution process data. Based on the resolution process data, the number of new connections and disconnections for each type of node in the resolution process are counted, the degree of modification of the connection relationship of each type of node is identified, and the connection reconstruction amount is obtained. Based on the process displacement and connection reconstruction amount, the path in the decomposition process data that meets the preset combination conditions is selected as the target process data chain, and the process execution sequence is generated.

[0021] In this embodiment of the invention, the process data chain of printing orders is obtained, providing a unified data foundation for subsequent node division, path analysis, and process reconstruction, avoiding inconsistencies between multi-source data. By dividing the process data chain into input nodes, transformation nodes, and output nodes, and extracting the predecessor and successor paths of each type of node to establish path participation identifiers, node process data is obtained. This process data simultaneously possesses node semantic information and path structure information, providing data support for subsequent calculations based on node type and path relationships. Based on the node process data, the process is extended along the predecessor and successor paths of the target node of the change instruction, establishing a connection hierarchy between each type of node and the target node, obtaining impact diffusion data, clarifying the degree of association between each node and the target node, and making the scope of process change have calculable boundaries in the data. Based on the impact diffusion data, different types of nodes at different connection levels are connected and reconstructed, and the path participation identifiers of each type of node are updated synchronously to obtain hierarchical reorganization data. This achieves partial reconstruction of the process structure while maintaining the stability of the parts not involved in the reorganization, avoiding a comprehensive modification of the entire data chain.

[0022] Based on the hierarchical reorganization data, the difference in the sequential number of each type of node in the process data chain and the hierarchical reorganization data is calculated to identify the degree of sequential offset after process reorganization, and the process displacement is obtained. This allows changes in node sequence and path affiliation to be expressed and compared numerically, providing a unified data basis for subsequent path selection. Based on the hierarchical reorganization data, path intersections generated during the reorganization process are identified, and path splitting is performed on type nodes with multiple predecessors or successors to obtain resolved process data. This eliminates connection ambiguities caused by path intersections and provides a data foundation for subsequent connection statistics and path selection. Based on the resolved process data, the number of new connections and disconnections for each type of node in the resolved process is counted, and the degree of modification of the connection relationship of each type of node is identified to obtain the connection reconstruction amount. This allows the connection changes during the process reorganization process to be quantified and, together with the process displacement, constitutes a two-dimensional data description of process changes. Based on the process displacement amount and the connection reconstruction amount, paths in the resolved process data that meet preset combination conditions are selected as target process data chains, generating process execution sequences. This realizes the transformation from multi-path structure data to single execution sequence data, giving the process data a directly executable sequential expression form.

[0023] The data chain for obtaining printing orders specifically includes: The system reads basic data corresponding to the target printing order from the printing business management system, order database, or process control platform. This basic data includes at least the order identifier, process configuration data, information on each process node, and the sequential relationships between processes. The system parses the read data, extracting each process involved in the process execution into independent node data units, assigning a unique node identifier to each node, and recording the process type, execution sequence number, and associated process parameters of the node. The system parses the dependencies between nodes, establishing connection relationship data between nodes by reading the original process configuration or process route definition, such as the predecessor node identifier, successor node identifier, and corresponding connection order. Then, all nodes are sorted according to their execution order, and the nodes and connections are combined to construct a chain-like data structure, i.e., a process data chain. During the construction process, the system performs unified processing on data from different sources, including field standardization, data format conversion, and missing value completion, to ensure the structural consistency of the node data, generating a process data chain object containing a set of nodes, a set of connections, and sequential relationships.

[0024] Specifically, by dividing the process data chain into input nodes, transformation nodes, and output nodes, and extracting the predecessor and successor paths of each type of node to establish path participation identifiers, node process data is obtained, including: The system traverses all nodes in the process data chain, classifying nodes based on their position and connections within the process. Nodes without predecessors or connected only to the start identifier are marked as input nodes; intermediate processing nodes with both predecessors and successors are marked as transformation nodes; and nodes without successors or connected only to the end identifier are marked as output nodes. The system extracts path information based on the connections between nodes. Starting from each node, it backtracks along its predecessor direction, recording the sequence of nodes traversed from the current node to the process start point, defining this sequence as the predecessor path of that node. Simultaneously, it traverses along its successor direction, recording the sequence of nodes traversed from the current node to the process end point, defining this sequence as the successor path of that node. The system assigns a path number to each path and records the order of nodes within the path. Based on the node's appearance in different paths, it establishes a path participation identifier for each node, which records the set of path numbers the node participates in and its positional relationship within each path. When the same node exists in multiple paths, its path participation identifier will contain multiple path numbers and corresponding position data. Combining the node type identifier, predecessor path data, successor path data, and path participation identifier yields the node flow data.

[0025] In a preferred embodiment of the present invention, based on node flow data, the connection hierarchy between various types of nodes and the target node is established by extending along the predecessor and successor paths of the target node of the change instruction, thereby obtaining influence diffusion data, including: Based on the node process data, identify the target node identifier in the change instruction, and extract the path participation identifier and path number of the target node to obtain the target node location data; Based on the target node location data, trace back adjacent nodes segment by segment along the predecessor path of the target node, and record the number of path segments traversed between the current node and the target node to obtain the predecessor extension data. Based on the target node location data, traverse adjacent nodes segment by segment along the successor path of the target node, and record the number of path segments traversed between the current node and the target node to obtain the successor extended data. Based on the predecessor and successor expansion data, the number of path segments is used as the connection level between each node and the target node. The node category identifier and path participation identifier are recorded to obtain the node level data. Based on the node hierarchy data, the node category identifier, path participation identifier, and connection level are combined and arranged in order of path number to obtain the impact diffusion data.

[0026] In this embodiment of the invention, based on node process data, the target node identifier in the change instruction is identified, and the path participation identifier and path number of the target node are extracted to obtain target node positioning data. This clearly indicates the target node's position, path affiliation, and participation status in the process network, providing a positioning basis for subsequent path expansion operations. Based on the target node positioning data, adjacent nodes are traced back segment by segment along the predecessor path of the target node, and the number of path segments traversed between the current node and the target node is recorded to obtain predecessor expansion data. This allows the relationship strength of each predecessor node relative to the target node to be represented numerically, establishing the upstream influence range. Based on the target node positioning data, adjacent nodes are traversed segment by segment along the successor path of the target node, and the number of path segments traversed between the current node and the target node is recorded to obtain successor expansion data. The data is expanded to clearly define the downstream impact range in terms of data hierarchy, forming a downstream related data structure centered on the target node. Based on the preceding and subsequent expansion data, the number of path segments is used as the connection level between each node and the target node. Node category identifiers and path participation identifiers are recorded to obtain node hierarchy data, making the relationship between nodes and target nodes appear as a connection and hierarchical relationship, providing a data basis for subsequent hierarchical grouping and processing. Based on the node hierarchy data, the node category identifiers, path participation identifiers, and connection levels are combined and arranged in order of path number to obtain impact diffusion data. This ensures that all nodes related to the target node in the process have a clear hierarchical order and path affiliation in the data, providing a data input structure for subsequent process reorganization.

[0027] Specifically, based on the target node's location data, adjacent nodes are traced back segment by segment along the target node's predecessor path, and the number of path segments traversed between the current node and the target node is recorded to obtain the predecessor extension data, which includes: Based on the target node location data, the system determines the target node's position index and its corresponding path number set in each path. For each path containing the target node, the system starts from the target node's location and visits its upstream nodes level by level in the predecessor direction. The system reads the target node's direct predecessor node identifier and locates the corresponding node object in the node flow data, treating this node as the first-level predecessor node. Simultaneously, it records the current path segment count as 1. The system uses this predecessor node as the new current node and continues searching for its predecessor node, incrementing the path segment count to 2, and so on, until the input node is reached or no predecessor node exists. During the backtracking process, the system creates a record for each visited node, including the node identifier, node category identifier, path number, node's position index in the path, and the corresponding path segment count. For the same node being backtracked in different paths, the system records the path segment count in each path. To avoid duplicate traversal, an access flag or caching mechanism is set to mark processed nodes and prevent them from being counted repeatedly in the same path. The backtracking results on all paths are summarized to form predecessor extended data.

[0028] Specifically, based on the target node's location data, adjacent nodes are traversed segment by segment along the target node's successor path, and the number of path segments traversed between the current node and the target node is recorded to obtain the successor extended data, which specifically includes: The system, also based on the target node's position in each path, traverses its downstream nodes level by level from the target node, reading the direct successor node identifier of the target node and locating the corresponding node object as the first-level successor node. Simultaneously, the number of path segments is initialized to 1. Using this node as the current node, the system continues searching for its successor node, incrementally increasing the number of path segments to form a sequence of successor nodes with 2, 3, etc., until the output node is reached or no successor node exists. During the traversal, the system establishes a record for each visited node, recording its node identifier, node category identifier, path number, path position index, and the number of path segments between it and the target node. For paths with branching structures, the system traverses each branch independently to ensure all possible successor paths are covered. Furthermore, for the same node appearing in different paths, the system records the number of path segments in each path. To avoid loops or repeated visits, node access status identifiers or path marking mechanisms are used for control. The traversal results of all paths are integrated to form subsequent extended data.

[0029] Specifically, based on the predecessor and successor expansion data, the number of path segments is used as the connection level between each node and the target node. Node category identifiers and path participation identifiers are recorded to obtain node-level data, which specifically includes: The system merges predecessor and successor extended data, integrating the two types of data according to node identifiers and uniformly processing duplicate nodes. Using path number as the distinguishing dimension, the system retains records of the same node across different paths separately. The system extracts the path segment count field from each record and defines it as the node's connection level relative to the target node. The number of path segments in the predecessor direction can be marked as a negative level or uniformly represented by an absolute level value, while the number of path segments in the successor direction is marked as a positive level. The node category identifier and the original path participation identifier are associated with this level of data, ensuring that each record simultaneously contains node identifier, node category, path number, path participation information, and connection level information. For the target node itself, the system can set its connection level to 0 and include it in the hierarchical data as a reference node. Data is grouped according to path number, and within each group, nodes are sorted according to the size of their connection levels, forming the node hierarchical data.

[0030] In a preferred embodiment of the present invention, based on the influence diffusion data, connections and reconstructions are performed for nodes of different connection levels, and the path participation identifiers of each type of node are updated synchronously to obtain hierarchical reorganization data, including: Based on the impact diffusion data, nodes with connection levels within the preset level range are classified as recombination nodes, and nodes with connection levels outside the preset level range are classified as maintenance nodes, thus obtaining node grouping data; Based on the node grouping data, the original predecessor connection records and the original successor connection records of the recombined nodes are removed one by one, and the connection positions after removal are marked to obtain the broken link position data. Based on the broken link location data, the reconstructed nodes are inserted sequentially into the broken link locations, and the predecessor and successor connections are re-established to obtain the reconstructed connection data. Based on the reconstructed connection data, the nodes are reconnected to the reconstructed connection data in the order they are in the process data chain, resulting in reconstructed connection structure data. Based on the recombined connection structure data, the predecessor path record and successor path record of the node whose connection has changed are extracted again, and the path participation identifier is updated to obtain hierarchical recombined data.

[0031] In this embodiment of the invention, based on the influence diffusion data, nodes with connection levels within a preset range are classified as recombining nodes, and nodes with connection levels outside the preset range are classified as maintaining nodes, resulting in node grouping data. This data distinguishes nodes requiring adjustment from those remaining unchanged, providing a data grouping basis for subsequent local recombining. Based on the node grouping data, the original predecessor and successor connection records of the recombining nodes are sequentially deactivated, and the deactivated connection positions are marked, resulting in broken link position data. This transforms the connection relationship from an implicit structure to explicit data, providing a positional information basis for subsequent connection reconstruction. Based on the broken link position data, the recombining nodes are sequentially inserted into the broken link positions. The process involves re-establishing predecessor and successor connections to obtain reconstructed connection data, enabling the process structure to transition from the old connection structure to the new one, ensuring that the data structure remains connected after reconstruction. Based on the reconstructed connection data, nodes are reconnected to the reconstructed connection data in their order within the process data chain, resulting in recombined connection structure data. This restores the complete process structure at the data level and ensures that the data in the unadjusted parts remains stable. Based on the recombined connection structure data, the predecessor and successor path records of nodes with connection changes are re-extracted, and the path participation identifiers are updated to obtain hierarchical recombined data, ensuring that there are no inconsistencies between the recombined process data structure and the path identifiers.

[0032] Based on the impact diffusion data, nodes with connection levels within a preset range are classified as recombining nodes, and nodes with connection levels outside the preset range are classified as maintaining nodes, resulting in node grouping data, specifically including: The system reads the node set from the impact diffusion data. Each record in this set contains a node identifier, node category identifier, path number, path participation identifier, and connection level information. Based on pre-defined level range parameters, such as a level interval or level threshold range, the system filters and judges each node one by one, determining whether the connection level of each node falls within the preset level range. For nodes that meet the conditions, they are marked as recombined nodes, and their position index and connection relationship information in the corresponding path are recorded. For nodes that do not meet the conditions, they are marked as preserved nodes, and their original connection relationships and path participation identifiers are retained without modification. The system groups nodes according to path numbers, so that the node partitioning results under the same path form independent data subsets. At the same time, the original predecessor node identifier and the original successor node identifier of each node are recorded, resulting in node grouping data.

[0033] Specifically, based on the broken link location data, the reconstructed nodes are sequentially inserted into the broken link locations, and the predecessor and successor connections are re-established to obtain the reconstructed connection data, which includes: The system identifies all recombined nodes based on node grouping data and reads their connection information in the original process data chain, including their original predecessor and successor nodes. It then disconnects the original connections of the recombined nodes, breaking the connection between the node and its original predecessor and successor nodes, and records the connection breakpoint information for each break point. This information includes the identifiers of the two ends of the broken connection and their position index in the process chain, forming broken chain position data. Based on the sorting order of the recombined nodes in the node grouping data (e.g., by path number and connection hierarchy), the system sequentially inserts the recombined nodes into the corresponding broken chain positions. The system re-establishes predecessor and successor connections for each recombined node, connecting it to the front and back nodes of the broken chain position and updating the corresponding connection records to create continuous connections in the new process structure. When multiple recombined nodes need to be inserted into the same broken chain region, the system inserts them one by one in a predetermined order, updating the connection relationship after each insertion to ensure the continuity of the connection chain. Based on the above processing, reconstructed connection data is formed.

[0034] Specifically, based on the reconstructed connection data, the nodes are reconnected to the reconstructed connection data in the order they appear in the process data chain, resulting in reconstructed connection structure data, which includes: The system reads the set of retained nodes, their original order information, and connection relationships. Following the order of the retained nodes in the original flow data chain, it processes each node one by one, determining its insertion position in the reconstructed connection structure. Based on the position of the original predecessor or successor node of each retained node in the reconstructed connection data, the system determines the connection interval where the retained node should be inserted and reconnects it to the corresponding nodes. During insertion, the system updates the predecessor and successor connection relationships of the retained nodes to ensure continuous connections with nodes in the current reconstructed connection structure. For cases where multiple retained nodes need to be inserted into the same region, the system inserts them one by one in their original order, updating the connection relationships after each insertion. After inserting all retained nodes, the system performs a complete traversal of the entire flow structure, verifying the continuity of all node connections, checking for broken chains or isolated nodes, and correcting any anomalies. The system then determines that all nodes are included and the connection relationships are complete, obtaining the reconstructed connection structure data.

[0035] In a preferred embodiment of the present invention, based on the hierarchical reorganization data, the difference in the sequential number of each type of node in the process data chain and the hierarchical reorganization data is calculated to identify the degree of sequential offset after process reorganization and obtain the process displacement amount, including: Based on the hierarchical reorganization data, the difference between the reorganization sequence numbers of each type of node is calculated to identify the degree of change in the execution order of each type of node before and after the process reorganization, and the sequence offset item is obtained. Based on the hierarchical reorganization data, the degree of linkage impact of each type of node on the cross-path structure when the order changes is calculated, and the span association term is obtained. Based on the hierarchical reorganization data, the difference between the path numbers of each type of node before and after reorganization is calculated, the degree of change in path affiliation of each type of node is identified, and the path migration item is obtained. By fusing sequence offset, span association, and path migration items, the overall offset of each type of node in terms of execution order, cross-path association, and path affiliation is identified, and the process displacement is obtained.

[0036] In this embodiment of the invention, based on the hierarchical reorganization data, the difference between the reorganization sequence numbers of each type of node is calculated to identify the degree of change in the execution order of each type of node before and after process reorganization, resulting in a sequence offset term. This allows the positional changes of nodes in the process to be quantified, enabling process structure changes to be described and analyzed through sequence data. Based on the hierarchical reorganization data, the degree of linkage impact of each type of node on the cross-path structure when the sequence changes occur is calculated to obtain a span association term. This allows the association changes of nodes between different paths to be expressed at the data level, supplementing structural change information beyond sequence offset. Based on the hierarchical reorganization data, the difference between the path numbers of each type of node before and after reorganization is calculated to identify the degree of change in path affiliation of each type of node, resulting in a path migration term. This allows the change of a node from one path to another to be clearly represented at the data level, forming a quantitative description of process path structure changes. The sequence offset term, span association term, and path migration term are fused to identify the overall offset degree of each type of node in terms of execution order, cross-path association, and path affiliation, resulting in a process displacement amount. This allows process structure changes to be expressed numerically, providing data basis for subsequent path selection and decision-making.

[0037] Specifically, based on the hierarchical reorganization data, the difference between the reorganization sequence numbers of each type of node is calculated to identify the degree of change in the execution order of each type of node before and after process reorganization, resulting in a sequence offset term; based on the hierarchical reorganization data, the degree of linkage impact of each type of node on the cross-path structure when the sequence changes is calculated, resulting in a span association term; based on the hierarchical reorganization data, the difference between the path numbers of each type of node before and after reorganization is calculated to identify the degree of change in path affiliation of each type of node, resulting in a path migration term; the sequence offset term, span association term, and path migration term are fused to identify the overall offset degree of each type of node in terms of execution order, cross-path association, and path affiliation, resulting in the process displacement, specifically including: The system establishes a correspondence between the original process data chain and the hierarchical reassembled data based on node identifiers. For each node, it extracts its sequential position in the original process and its sequential position in the reassembled process. The sequence offset is calculated by subtracting the original position from the reassembled position, yielding the forward or backward movement of the node. To avoid the influence of positive or negative directions on subsequent statistics, the system takes the absolute value of this difference as the offset magnitude and accumulates or averages the offset magnitudes of all nodes within the same path to obtain the total sequence offset for that path. For multi-path structures, the system calculates the total sequence offset for each path separately and finally summarizes the offset results of all paths to form an overall sequence offset value. This value directly reflects the scale of change in the execution order dimension of the process.

[0038] For each node, the system extracts its predecessor and successor node sets before and after reorganization, and compares these two sets of connections. The system counts the number of changes in connected objects, i.e., the sum of the number of lost connections and the number of new connections in the original connections, as the connection change quantity. The system then analyzes whether these connection changes involve connections between different paths; for example, nodes originally connected to the same path may be connected to other paths after reorganization, or cross-path connections may be re-merged. For each connection with a cross-path change, the system records the degree of path difference, such as path number differences or path span ranges, and accumulates all cross-path connection changes. The system combines the number of connection changes with the degree of path span change, for example, by first summing them separately and then weighting them according to a preset ratio to obtain a span association term. This value represents the degree of path structure linkage change caused by the sequence change.

[0039] The system extracts the path attribution information of each node in the original process and its path attribution information in the reorganized process, and compares the two information one by one. For nodes belonging to only a single path, the system directly determines whether its path number has changed and uses the difference between the path numbers as the migration magnitude. For nodes participating in multiple paths, the system compares the changes in its path set, including the number of newly added paths, the number of removed paths, and changes in path numbers. The system counts the number of newly added or disappeared paths in the path set as the migration quantity, then calculates the magnitude of the path number change, and combines these two sets of data, for example, by first summing them separately and then performing unified processing to obtain the path migration value. The system accumulates or averages the path migration values ​​of all nodes to obtain the overall path migration item value, which reflects the degree of change in the process at the path attribution level.

[0040] The system performs uniform scaling on sequence offset, span correlation, and path migration terms, such as converting them to values ​​within the same range, to avoid bias in the results caused by any single value being too large or too small. The system combines these three data items according to preset weights. The structure involves multiplying each of the three values ​​by its corresponding weight and then summing them. The sequence offset term corresponds to the sequence change weight, the span correlation term corresponds to the path structure change weight, and the path migration term corresponds to the path affiliation change weight. The system performs this combined calculation for each node to obtain the node-level process displacement value. Then, it aggregates the process displacement values ​​of all nodes, for example, by summing or averaging to obtain the overall process displacement.

[0041] In a preferred embodiment of the present invention, based on the hierarchical recombination data, path intersections generated during the recombination process are identified, and path splitting is performed on type nodes with multiple predecessors or multiple successors to obtain resolution process data, including: Based on the hierarchical reorganization data, nodes with multiple predecessor or successor connection records are selected and marked as intersection nodes. At the same time, the connection combination relationship is recorded to obtain the path intersection node data. Based on the path intersection node data, each predecessor connection record and each successor connection record are paired into independent connection relationships to obtain connection combination data; Based on the connection combination data, the cross nodes are replaced with multiple independent nodes, and an identifier is assigned to each independent node. The node category identifier and path participation identifier of the cross nodes are inherited to obtain the node splitting data. Based on the node-splitting data, the independent nodes are re-embedded into the hierarchical reorganization data according to the connection and combination relationship to obtain the resolution process data.

[0042] In this embodiment of the invention, based on the hierarchical reorganization data, nodes with multiple predecessor or successor connection records are selected and marked as intersection nodes. Simultaneously, connection combination relationships are recorded to obtain path intersection node data. Nodes with multiple connection relationships are identified, and their complex connection relationships are transformed into enumerable connection combination data, providing a data foundation for subsequent connection splitting. Based on the path intersection node data, each predecessor connection record and each successor connection record are paired as independent connection relationships to obtain connection combination data, thus expanding the complex many-to-many connection structure into multiple one-to-one connection units at the data level. Based on the connection combination data, intersection nodes are replaced with multiple independent nodes, and each independent node is assigned an identifier, inheriting the node category identifier and path participation identifier of the intersection node, to obtain node splitting data. This transforms a node with multiple connection relationships into multiple nodes with only a single connection relationship, eliminating data ambiguity caused by multiple connections. Based on the node splitting data, independent nodes are re-embedded into the hierarchical reorganization data according to connection combination relationships to obtain resolution process data, eliminating structural uncertainty caused by path intersections and providing a data foundation for subsequent connection statistics and path filtering.

[0043] Specifically, based on the hierarchical reorganization data, nodes with multiple predecessor or successor connection records are selected and marked as intersection nodes. At the same time, the connection combination relationship is recorded to obtain path intersection node data, which includes: The system iterates through the node set in the hierarchical reorganization data, reading the connection relationship information of each node, including its predecessor connection record set and successor connection record set. The system counts the number of predecessor and successor connections for each node. When a node is found to have more than one predecessor connection or more than one successor connection, it is identified as a cross node. Subsequently, the system extracts all predecessor and successor connection node identifiers for this cross node and further reads the path number, node position index, and connection order information corresponding to these connections. The system registers the combination relationships of all predecessor and successor connections of this cross node, forming a combined structure of predecessor and successor connection sets, and assigns a unique identifier to each combination relationship. The system retains the node category identifier and path participation identifier of this node, allowing it to inherit the original semantic information during subsequent splitting. For cases where the same node appears in different paths, the system performs the above filtering and recording operations under each path dimension to generate path cross node data.

[0044] Specifically, based on the path intersection node data, each predecessor connection record and each successor connection record are paired into independent connection relationships to obtain connection combination data, which includes: For each intersection node in the path intersection node data, the system reads its predecessor connection set and successor connection set, and performs connection combination processing. Each predecessor node in the predecessor connection set is paired with each successor node in the successor connection set, generating multiple independent connection relationships. For each pairing result, an independent connection record is created, containing the predecessor node identifier, successor node identifier, path number, and connection order information. While generating connection combinations, the system assigns a unique combination number to each connection relationship and records its source intersection node identifier. In cases of multiple path intersections, the system performs combination processing according to the path number, ensuring that connection relationships between different paths are not mixed. For cases where the same predecessor node corresponds to multiple successor nodes or the same successor node corresponds to multiple predecessor nodes, the system generates a complete set of connection relationships through full combination, avoiding the omission of any possible connection paths. This results in connection combination data, which consists of multiple independent connection relationships, each of which is a combination of a single predecessor node and a single successor node.

[0045] Specifically, based on the connection combination data, the cross nodes are replaced with multiple independent nodes, and an identifier is assigned to each independent node. The node category identifier and path participation identifier of the cross nodes are inherited to obtain the node splitting data, which includes: The system generates a new node instance for each independent connection in the connection combination data, replacing the original cross node. For each connection combination, the system creates an independent node, assigns it a new unique node identifier, and records its source cross node identifier. The system sets the predecessor connection of the new node to the predecessor node in the corresponding combination and its successor connection to the successor node in the corresponding combination, ensuring that the node retains only one explicit set of connections. Regarding node attributes, the system copies the node category identifier of the original cross node to the new node and inherits its path participation identifier. Simultaneously, it updates the path participation identifier based on the path numbers involved in the current connection combination, ensuring that the new node corresponds only to the paths it actually participates in. In the data structure, the connection relationships of the original cross node are gradually replaced by the connection relationships of multiple new nodes. The system maintains the mapping relationship between the original nodes and new nodes for subsequent data tracking or consistency verification. For cross nodes with multiple connection combinations, the system repeats the above node generation process until all combination relationships are converted into independent nodes, resulting in node-split data. This data represents a set of multiple independent nodes, each node corresponding to a single set of connections, completing the structural splitting of the cross nodes.

[0046] In a preferred embodiment of the present invention, based on the resolution process data, the number of new connections and the number of broken connections for each type of node in the resolution process are statistically analyzed to identify the degree of modification of the connection relationships of each type of node, and the connection reconstruction amount is obtained, including: Based on the resolution process data, the number of new connections and disconnections for each type of node in the resolution process are counted, the basic degree of connection modification for each type of node in the resolution process is identified, and the connection rewriting items are obtained. Based on the resolution process data, the degree of deviation between connection increase and connection termination during the connection reconstruction process of each type of node is calculated to obtain the connection imbalance term. Based on the resolution process data, the degree of expansion of the connection structure caused by the combined effects of path splitting and path participation changes of each type of node is calculated to obtain the path expansion term. By fusing connection rewriting, connection imbalance, and path expansion items, the comprehensive reconstruction degree of each type of node in terms of connection rewriting, connection imbalance, and path impact is identified, and the connection reconstruction quantity is obtained.

[0047] In this embodiment of the invention, based on the resolution process data, the number of new connections and disconnections for each type of node in the resolution process are statistically analyzed to identify the basic degree of connection modification for each type of node in the resolution process, thus obtaining a connection rewriting term. This allows changes in node connection relationships to be expressed in quantitative form, forming a basic data description of process connection modifications. Based on the resolution process data, the deviation between connection increases and disconnections for each type of node during connection reconstruction is calculated, resulting in a connection imbalance term. This makes connection changes manifest as differences in quantity, direction, and degree of change, forming a more granular connection... Based on the description of the change data, and according to the resolution process data, the degree of expansion of the connection structure caused by the combined effects of path splitting and path participation changes of each type of node is calculated to obtain the path expansion item. This allows the expansion of the process in the path dimension to be clearly recorded, supplementing the data expression of connection changes at the path structure level. The connection rewriting item, connection imbalance item, and path expansion item are integrated to identify the comprehensive reconstruction degree of each type of node in terms of connection rewriting, connection imbalance, and path impact, obtaining the connection reconstruction quantity. This allows the reconstruction degree of the process connection relationship to be expressed numerically, providing data basis for subsequent path selection and process optimization.

[0048] Specifically, based on the resolution process data, the number of new connections and disconnections for each type of node during the resolution process is statistically analyzed to identify the basic degree of connection modification for each type of node during the resolution process, thus obtaining the connection rewriting item; based on the resolution process data, the deviation between the increase and decrease of connections for each type of node during the connection reconstruction process is calculated, thus obtaining the connection imbalance item; based on the resolution process data, the degree of expansion of the connection structure by each type of node under the combined effect of path splitting and path participation changes is calculated, thus obtaining the path expansion item; the connection rewriting item, connection imbalance item, and path expansion item are fused to identify the comprehensive reconstruction degree of each type of node in terms of connection rewriting, connection imbalance, and path impact, thus obtaining the connection reconstruction quantity, specifically including: The system uses node identifiers as indexes to extract the set of connection relationships corresponding to each node from the resolution process data and the hierarchical reorganization data, respectively. For each node, the system reads its predecessor and successor connection sets in the original structure, and simultaneously reads its corresponding connection set in the resolution process, comparing the two sets of connection relationships one by one. The system identifies connections that exist in the resolution process but not in the original connection set as new connections and counts these connections; it also identifies connections that exist in the original connection set but no longer exist in the resolution process as broken connections and counts these connections as well. For each node, the system records the number of new connections and the number of broken connections, and can combine the two statistics, for example, by directly summing them to form the total number of connection changes, or retaining them separately for subsequent calculations to obtain a connection rewriting item, which is used to characterize the basic changes in the number of connection relationships at the node.

[0049] The system compares the number of new connections and the number of broken connections for each node, calculating the difference and its direction. When the number of new connections exceeds the number of broken connections, the system records that the node's connections are increasing; when the number of broken connections exceeds the number of new connections, it records a decreasing trend; and when the two are close, it records a relatively balanced state. Simultaneously, the system calculates the ratio between new and broken connections to further characterize the degree of deviation in connection changes. For all nodes, the above differences or ratios are uniformly processed, such as taking the absolute difference or normalizing to form connection imbalance data. The system summarizes the connection imbalance data of all nodes or groups and statistically analyzes it by path to obtain a connection imbalance item, which describes the degree of structural imbalance in connection changes.

[0050] The system identifies the path participation of each node before and after path splitting, reading the number of paths it participated in in the original process and the number of paths its corresponding node participated in in the resolution process. For node splitting, the system associates the original node with multiple new nodes and counts the number of newly added path participations after the split. Simultaneously, the system counts the number of new connection paths introduced by the node split, i.e., paths originally connected by a single node become multiple independent path connections after the split. The system combines the changes in the number of path participations with the number of new path connections, for example, by summing them or weighting them according to a certain ratio, to obtain the degree of expansion of the node in the path dimension. For the entire process, the system summarizes or averages the path expansion data of all nodes to form a path expansion item, which describes the expansion changes of the process at the path structure level.

[0051] The system maps connection rewriting, connection imbalance, and path expansion items to the same data scale, for example, by using a unified numerical range conversion to make data from different sources comparable. Then, the system integrates the corresponding connection rewriting, connection imbalance, and path expansion values ​​for each node, and calculates them according to a preset combination rule. This combination rule can be understood as assigning weights to each of the three data items and then summing them to form a node-level comprehensive connection change value. During the calculation process, the weights can be adjusted according to the node category or path importance to reflect the different impacts of different nodes on the process structure. The comprehensive connection change values ​​of all nodes are then summarized, for example, by summing or averaging to obtain the overall connection reconstruction amount, which is used as the final data result to characterize the overall degree of change in the process connection relationship.

[0052] In a preferred embodiment of the present invention, based on the process displacement and connection reconstruction amount, a path in the decrypted process data that satisfies a preset combination condition is selected as the target process data chain, and a process execution sequence is generated, including: Based on the digestion process data, the node connection relationships in each path are extracted and divided according to the path number. The node set and connection structure of each path are recorded to obtain the path structure data. Based on the path structure data, the process displacement and connection reconstruction amount in each path are weighted and fused to calculate the fused path value and obtain the path numerical mapping data. Based on the path numerical mapping data, the fused path value of each path is compared with the preset combination conditions, and the paths that meet the preset combination conditions are selected to obtain candidate path data. Based on the candidate path data, the parts of the path with duplicate nodes or conflicting connections are removed, and the node sequence with continuous connection is retained to obtain the target path data; Based on the target path data, each node is expanded sequentially according to its predecessor and successor connections, and then sorted by path number to generate a process execution sequence.

[0053] In this embodiment of the invention, based on the resolution process data, the node connection relationships in each path are extracted and divided according to the path number. The node set and connection structure of each path are recorded to obtain path structure data. The overall process structure in the resolution process data is split into multiple independent path structures, providing basic data for subsequent path-level calculation and selection. Based on the path structure data, the process displacement and connection reconstruction amounts in each path are weighted and fused to calculate the fused path value, obtaining path numerical mapping data. This allows the comprehensive situation of each path in terms of both sequence change and connection change to be represented by a single value, achieving unified quantitative comparison between paths. Based on the path numerical mapping data, the fused path value of each path is compared with preset combination conditions. The process involves comparing and selecting paths that meet preset combination conditions to obtain candidate path data. Multiple candidate paths are then filtered to achieve constraint control in path selection. Based on the candidate path data, duplicate nodes or conflicting connections are removed, while continuous node sequences are retained to obtain the target path data. Abnormal structures in the candidate paths are cleaned up to ensure consistency and continuity in the path structure data. Based on the target path data, each node is expanded sequentially according to its predecessor and successor connections, and then sorted by path number to generate a process execution sequence. This transforms the path structure data into a linear execution sequence, converting the process data from a graph structure to a sequential structure for direct execution.

[0054] Specifically, based on the path structure data, the process displacement and connection reconstruction amounts in each path are weighted and fused to calculate the fused path value, resulting in path numerical mapping data, which includes: The system reads the set of path nodes and connection structure divided by path number from the path structure data. For each path, it extracts all node identifiers. Using the node identifier as an index, the system extracts the numerical results of the corresponding nodes from the process displacement data and connection reconstruction data obtained in the previous steps, and aggregates the values ​​of nodes belonging to the same path. For process displacement, the system calculates the comprehensive displacement data of each node within the path in terms of changes in execution order, path affiliation, and cross-path linkage. It then accumulates, averages, or weights the displacement values ​​of each node according to its position to form a path-level process displacement value. For connection reconstruction, the system calculates the comprehensive reconstruction data of each node within the path in terms of adding connections, disconnecting connections, connection imbalance, and path expansion. It then accumulates, averages, or weights the reconstruction values ​​of each node according to its importance to form a path-level connection reconstruction value. The system performs weighted fusion of path-level process displacement values ​​and path-level connection reconstruction values ​​according to preset weighting rules. The path-level process displacement values ​​are recalculated using a first weight, and the path-level connection reconstruction values ​​are recalculated using a second weight. The two recalculated values ​​are then merged to form the fused path value for that path. If the system is preset to be more sensitive to sequence changes, the first weight is relatively larger; if the system is preset to be more sensitive to the stability of the connection structure, the second weight is relatively larger. For all paths, the system repeats the above value extraction, path-level aggregation, and weighted fusion processing, and establishes a mapping relationship between the path number of each path and the corresponding fused path value, generating path value mapping data.

[0055] Specifically, based on the path numerical mapping data, the fused path value of each path is compared with preset combination conditions to filter out paths that meet the preset combination conditions, thus obtaining candidate path data, which specifically includes: The system reads the fused path values ​​corresponding to each path in the path numerical mapping data and calls the pre-set combination condition parameters. The pre-set combination conditions can be a single condition or a composite filtering rule formed by combining multiple conditions. These pre-set combination conditions can include upper limit conditions, lower limit conditions, interval conditions, sorting conditions, and joint judgment conditions combined with path length, number of nodes, and retention status of key nodes. The system performs condition judgments for each path sequentially. First, it compares whether the fused path value of the path is within a preset allowable range. If it is not within the range, the path is marked as not meeting the conditions and eliminated. If it is within the allowable range, it continues to judge whether the path meets other additional conditions, such as whether the target node is retained, whether it contains necessary process nodes, whether the path length exceeds the allowable range, and whether there are structural change nodes in the path exceeding a predetermined number. For sorting and filtering, the system first sorts all paths according to their fused path values, and then selects paths whose values ​​are within a predetermined ranking range as candidates. For multi-condition joint filtering, the system filters layer by layer in the order of first filtering by numerical thresholds and then judging structural constraints, reducing the number of invalid paths participating in subsequent processing. Whenever a path meets all the preset combination conditions, the system writes the path number, node set, connection structure and corresponding fusion path value of the path into the candidate path data; for paths that do not meet the conditions, only the filtering log or status identifier is retained and they are not included in the candidate set, thus obtaining candidate path data. This data is used to characterize the set of alternative paths that meet both numerical and structural constraints in the current process reorganization result.

[0056] Specifically, based on the candidate path data, duplicate nodes or conflicting connections in the path are removed, and the sequence of nodes with continuous connections is retained to obtain the target path data, which includes: The system performs structural verification on each candidate path in the candidate path data, checking its node sequence and connection relationship records in turn. For duplicate nodes, the system compares node identifiers to identify whether the same node appears twice or more in the same path. When duplicate nodes are found, the system further analyzes whether the predecessor and successor connections corresponding to each duplicate node are consistent. If a duplicate record is only used as an intermediate retention result in the cross-resolve or path splitting process and does not affect the main chain connectivity, the duplicate record is deleted first. If duplicate nodes connect to different chain segments, the system compares the continuity of each chain segment, the consistency of path numbering, and the relevance of target nodes, retaining the record that best fits the current main structure of the path and removing the remaining duplicate records. For conflicting connections, the system checks the predecessor and successor connection relationships between nodes one by one to identify whether the following situations exist: the same node corresponds to multiple predecessor nodes that should not coexist, the same node corresponds to multiple successor nodes that should not coexist, the connection direction is inconsistent with the overall path expansion direction, local connections form loops, and a connection crosses a determined continuous chain segment, causing the order to reverse, etc. When conflicting connections are detected, the system, based on the original path order, the continuity of connections in candidate paths, and prior selection criteria, removes connections that do not meet the requirements for continuous expansion, retaining only a set of connections that maintain the logical continuity between nodes. After completing the cleanup of duplicate nodes and elimination of conflicting connections, the system starts from the path's starting node and performs a connectivity traversal on the retained nodes, extracting a sequence of nodes with continuous predecessor and successor relationships. For isolated nodes, broken segments, or local sub-chains that cannot be connected to the main chain due to the removal operation, the system removes them from the current path. If multiple continuous segments exist in the path, the system can select the most suitable segment as a valid sequence based on the segment length, target node coverage, or degree of conformity with the original flow order, obtaining the target path data. Each path in this data represents a continuous node sequence without duplicate nodes or connection conflicts.

[0057] Specifically, based on the target path data, each node is expanded sequentially according to its predecessor and successor connections, and then sorted by path number to generate a process execution sequence, which includes: The system reads the node set of each target path in the target path data, along with its predecessor and successor connections. Within each target path, it identifies the starting node, which is typically a node without a predecessor connection record, or whose predecessor only points to the path entry identifier. After determining the starting node, the system traverses its subsequent nodes level by level along the successor connection relationship. Each visited node is written into the execution sequence cache of the current path, and its expansion order within the path is recorded synchronously. For each written node, the system continues to read its successor nodes until it reaches the end node with no successor connection record, thus forming an ordered node execution chain within a single path. If multiple expandable sub-sequences exist in parallel within the target path, the system sorts them according to the connection priority retained in the path, the original process order, or the node position index under the path number, ensuring that the final generated execution chain within the path retains only one definite expansion order. After unfolding the node sequence within each path, the system sorts multiple target paths according to their path numbers, arranging them from smallest to largest. Alternatively, it can use preset business rules to determine a priority order, prioritizing main paths and placing branch paths later. The system organizes the node execution chains within each path sequentially according to their path numbers, forming a process execution sequence. The system can also perform consistency checks on the process execution sequence, checking for missing nodes, duplicate nodes, or breaks in the execution order. If any anomalies are detected, the corresponding target path data is backtracked and re-corrected.

[0058] Embodiments of the present invention also provide a digital-based dynamic workflow management system for printing information, the system comprising: The data module is used to obtain the process data chain of printing orders; The node module is used to divide the process data chain into input nodes, transformation nodes, and output nodes, and extract the predecessor and successor paths of each type of node to establish path participation identifiers, thereby obtaining node process data. The connection module is used to expand along the predecessor and successor paths of the target node of the change instruction based on the node process data, establish the connection hierarchy between various types of nodes and the target node, and obtain the impact diffusion data. The reorganization module is used to connect and rebuild nodes of different connection levels according to the impact diffusion data, and to update the path participation identifiers of each type of node simultaneously to obtain hierarchical reorganization data. The displacement module is used to calculate the difference in the sequential number of each type of node in the process data chain and the hierarchical reorganization data based on the hierarchical reorganization data, identify the degree of sequential offset after process reorganization, and obtain the process displacement amount. The splitting module is used to identify path intersections during the reorganization process based on the hierarchical reorganization data, and to split the paths of type nodes with multiple predecessors or multiple successors to obtain the resolution process data. The reconstruction module is used to count the number of new connections and disconnections of each type of node in the resolution process based on the resolution process data, identify the degree of modification of the connection relationship of each type of node, and obtain the connection reconstruction quantity. The process module is used to select the path in the decomposition process data that meets the preset combination conditions as the target process data chain based on the process displacement and connection reconstruction amount, and generate the process execution sequence.

[0059] It should be noted that this system is a system corresponding to the above method. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0060] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0061] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0062] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A digital-based dynamic workflow management method for printing information, characterized in that: The method includes: The process data chain for obtaining printing orders; By dividing the process data chain into input nodes, transformation nodes, and output nodes, and extracting the predecessor and successor paths of each type of node to establish path participation identifiers, node process data is obtained. Based on the node process data, identify the target node identifier in the change instruction, and extract the path participation identifier and path number of the target node to obtain the target node location data; Based on the target node location data, trace back adjacent nodes segment by segment along the predecessor path of the target node, and record the number of path segments traversed between the current node and the target node to obtain the predecessor extension data. Based on the target node location data, traverse adjacent nodes segment by segment along the successor path of the target node, and record the number of path segments traversed between the current node and the target node to obtain the successor extended data. Based on the predecessor and successor expansion data, the number of path segments is used as the connection level between each node and the target node. The node category identifier and path participation identifier are recorded to obtain the node level data. Based on the node hierarchy data, the node category identifier, path participation identifier, and connection level are combined and arranged in order of path number to obtain the impact diffusion data. Based on the impact diffusion data, nodes with connection levels within the preset level range are classified as recombination nodes, and nodes with connection levels outside the preset level range are classified as maintenance nodes, thus obtaining node grouping data; Based on the node grouping data, the original predecessor connection records and the original successor connection records of the recombined nodes are removed one by one, and the connection positions after removal are marked to obtain the broken link position data. Based on the broken link location data, the reconstructed nodes are inserted sequentially into the broken link locations, and the predecessor and successor connections are re-established to obtain the reconstructed connection data. Based on the reconstructed connection data, the nodes are reconnected to the reconstructed connection data in the order they are in the process data chain, resulting in reconstructed connection structure data. Based on the reconstructed connection structure data, the predecessor path record and successor path record of the node whose connection has changed are re-extracted, and the path participation identifier is updated to obtain hierarchical reconstructed data. Based on the hierarchical reorganization data, calculate the difference in the sequential number of each type of node in the process data chain and the hierarchical reorganization data, identify the degree of sequential offset after process reorganization, and obtain the process displacement. Based on the hierarchical reorganization data, identify the path intersections that occur during the reorganization process, and split the path of type nodes with multiple predecessors or multiple successors to obtain the resolution process data. Based on the resolution process data, the number of new connections and disconnections for each type of node in the resolution process are counted, the degree of modification of the connection relationship of each type of node is identified, and the connection reconstruction amount is obtained. Based on the process displacement and connection reconstruction amount, the path in the decomposition process data that meets the preset combination conditions is selected as the target process data chain, and the process execution sequence is generated.

2. The method for dynamic workflow management of printing information based on digitalization according to claim 1, characterized in that, Based on the hierarchical reorganization data, calculate the difference in the sequential number of each type of node in the process data chain and the hierarchical reorganization data, identify the degree of sequential offset after process reorganization, and obtain the process displacement, including: Based on the hierarchical reorganization data, the difference between the reorganization sequence numbers of each type of node is calculated to identify the degree of change in the execution order of each type of node before and after the process reorganization, and the sequence offset item is obtained. Based on the hierarchical reorganization data, the degree of linkage impact of each type of node on the cross-path structure when the order changes is calculated, and the span correlation term is obtained. Based on the hierarchical reorganization data, the difference between the path numbers of each type of node before and after reorganization is calculated, the degree of change in path affiliation of each type of node is identified, and the path migration item is obtained. By fusing sequence offset, span association, and path migration items, the overall offset of each type of node in terms of execution order, cross-path association, and path affiliation is identified, and the process displacement is obtained.

3. The method for dynamic workflow management of printing information based on digitalization according to claim 2, characterized in that, Based on the hierarchical reorganization data, path intersections during the reorganization process are identified, and path splitting is performed on nodes with multiple predecessors or successors to obtain resolution process data, including: Based on the hierarchical reorganization data, nodes with multiple predecessor or successor connection records are selected and marked as intersection nodes. At the same time, the connection combination relationship is recorded to obtain the path intersection node data. Based on the path intersection node data, each predecessor connection record and each successor connection record are paired into independent connection relationships to obtain connection combination data; Based on the connection combination data, the cross nodes are replaced with multiple independent nodes, and an identifier is assigned to each independent node. The node category identifier and path participation identifier of the cross nodes are inherited to obtain the node splitting data. Based on the node-splitting data, the independent nodes are re-embedded into the hierarchical reorganization data according to the connection and combination relationship to obtain the resolution process data.

4. The digital-based dynamic workflow management method for printing information according to claim 3, characterized in that, Based on the resolution process data, the number of new connections and disconnections for each type of node during the resolution process is statistically analyzed to identify the degree of modification of connection relationships for each type of node, thus obtaining the connection reconstruction quantity, including: Based on the resolution process data, the number of new connections and disconnections for each type of node in the resolution process are counted, the basic degree of connection modification for each type of node in the resolution process is identified, and the connection rewriting items are obtained. Based on the resolution process data, the degree of deviation between connection increase and connection termination during the connection reconstruction process of each type of node is calculated to obtain the connection imbalance term. Based on the resolution process data, the degree of expansion of the connection structure caused by the combined effects of path splitting and path participation changes of each type of node is calculated to obtain the path expansion term. By fusing connection rewriting, connection imbalance, and path expansion items, the comprehensive reconstruction degree of each type of node in terms of connection rewriting, connection imbalance, and path impact is identified, and the connection reconstruction quantity is obtained.

5. The digital-based dynamic workflow management method for printing information according to claim 4, characterized in that, Based on the process displacement and connection reconstruction amount, the path in the decompiled process data that meets the preset combination conditions is selected as the target process data chain, and a process execution sequence is generated, including: Based on the digestion process data, the node connection relationships in each path are extracted and divided according to the path number. The node set and connection structure of each path are recorded to obtain the path structure data. Based on the path structure data, the process displacement and connection reconstruction amount in each path are weighted and fused to calculate the fused path value and obtain the path numerical mapping data. Based on the path numerical mapping data, the fused path value of each path is compared with the preset combination conditions, and the paths that meet the preset combination conditions are selected to obtain candidate path data. Based on the candidate path data, the parts of the path with duplicate nodes or conflicting connections are removed, and the node sequence with continuous connection is retained to obtain the target path data; Based on the target path data, each node is expanded sequentially according to its predecessor and successor connections, and then sorted by path number to generate a process execution sequence.

6. A digital-based dynamic workflow management system for printing information, characterized in that: The system is used to perform the method as described in any one of claims 1 to 4, the system comprising: The data module is used to obtain the process data chain of printing orders; The node module is used to divide the process data chain into input nodes, transformation nodes, and output nodes, and extract the predecessor and successor paths of each type of node to establish path participation identifiers, thereby obtaining node process data. The connection module is used to expand along the predecessor and successor paths of the target node of the change instruction based on the node process data, establish the connection hierarchy between various types of nodes and the target node, and obtain the impact diffusion data. The reorganization module is used to connect and rebuild nodes of different connection levels according to the impact diffusion data, and to update the path participation identifiers of each type of node simultaneously to obtain hierarchical reorganization data. The displacement module is used to calculate the difference in the sequential number of each type of node in the process data chain and the hierarchical reorganization data based on the hierarchical reorganization data, identify the degree of sequential offset after process reorganization, and obtain the process displacement amount. The splitting module is used to identify path intersections during the reorganization process based on the hierarchical reorganization data, and to split the paths of type nodes with multiple predecessors or multiple successors to obtain the resolution process data. The reconstruction module is used to count the number of new connections and disconnections of each type of node in the resolution process based on the resolution process data, identify the degree of modification of the connection relationship of each type of node, and obtain the connection reconstruction quantity. The process module is used to select the path in the decompiled process data that meets the preset combination conditions as the target process data chain based on the process displacement and connection reconstruction amount, and generate the process execution sequence.

7. A computing device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program that, when executed by a processor, implements the method as described in any one of claims 1 to 5.

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