Self-service ticket terminal task automation guide processing method

Abstract

This invention belongs to the field of self-service ticketing technology, specifically relating to an automated task guidance processing method for self-service ticketing terminals. The method includes: constructing a parameter dependency graph in the form of a directed acyclic graph (DAG), and determining the guidance filling order based on topological sorting results; obtaining a set of feasible values, calculating the subsequent conflict risk coefficient of each candidate value in the feasible value set, and sorting and displaying the candidate values; calculating the backtracking cost coefficient of each candidate backtracking predecessor node, and determining the minimum backtracking target node based on the backtracking cost coefficient to perform fixed-point backtracking; after all parameter nodes in the parameter dependency graph have been verified, serializing the parameter value set of the current session into a task snapshot with a version stamp, and submitting a ticketing request to the backend order service using the task snapshot as an idempotent key. This invention effectively shortens the time point for conflict exposure and reduces the length of the user's operation path in conflict scenarios.

Description

Technical Field

[0001] This invention belongs to the field of self-service ticketing technology, specifically relating to a method for automated task guidance processing of self-service ticketing terminals. Background Technology

[0002] Self-service ticketing terminals are widely deployed in public places such as transportation hubs, cinemas, and scenic spots, undertaking the core function of replacing manual ticket windows and alleviating the pressure of ticket purchases. As peak passenger flow becomes increasingly concentrated, the terminal's interaction efficiency and task completion rate directly affect the passenger experience and venue operating costs.

[0003] Patent document CN116680745B discloses an automatic ticketing method and system, comprising: generating a first time threshold and a second time threshold by a ticketing terminal; receiving ticket booking information sent by a user by the ticketing terminal; after receiving the ticket booking information sent by the user, sending the ticket booking information to a server by the ticketing terminal, and starting a timer by the ticketing terminal; after sending the ticket booking information to the server by the ticketing terminal, waiting for feedback from the server by the ticketing terminal; if the ticketing terminal receives the first feedback from the server, determining whether the first count of the current timer is greater than the first time threshold; if the ticketing terminal determines that the first count of the timer is less than the first time threshold, providing the user with payment information and at least part of the ticket booking information by the ticketing terminal.

[0004] Existing self-service ticketing terminals have made some improvements in interactive guidance. Some terminals have introduced voice prompts, gradually informing users of the current fields to be filled in via voice; others use keyword recognition technology to parse simple voice commands from users and jump to the corresponding menu nodes; mainstream products break down the ticketing task into a multi-level menu tree with a fixed order, guiding users to select parameters such as departure point, destination, date, seat class, and number of people step by step before entering the payment process.

[0005] However, all the aforementioned terminals model the parameter collection process as a linear sequential state machine in their ticket purchase task guidance, with each parameter slot filled independently and without dependencies between them. Since user ticket purchase requests may involve multi-dimensional constraints, such as specifying a particular train number, seat class, multiple passengers, and requiring adjacent seats, this linear sequential state machine model may cause the terminal to fail to predict the feasibility of parameter combinations during the guidance phase. Instead, it completely postpones the detection of cross-parameter constraint conflicts to the final transaction commit phase, where the backend ticketing system performs inventory verification. Once a conflict is detected, the system triggers a full session rollback, clearing all collected parameters and forcing the user to re-enter the complete ticket purchase process from scratch. During peak travel periods, this full rollback mode increases terminal downtime and user abandonment rates, thus creating a business bottleneck. Summary of the Invention

[0006] This invention provides an automated task guidance processing method for self-service ticketing terminals to solve the technical problem in the prior art that the delay in cross-parameter constraint conflict detection in self-service ticketing terminals leads to full session rollback and users having to re-enter information from scratch.

[0007] This invention provides an automated task guidance method for self-service ticketing terminals, comprising the following steps: S1 responds to the ticket purchase request by parsing the input content to extract parameter slots, constructs a parameter dependency graph in the form of a directed acyclic graph for the parameter slots according to the ticketing business rules, and determines the filling order based on the topological sorting result; S2, perform feasible region shrinkage operation on the parameter nodes in the parameter dependency graph layer by layer according to the guided filling order to obtain a feasible value set, calculate the subsequent conflict risk coefficient of each candidate value in the feasible value set, and sort and display the candidate values ​​according to the subsequent conflict risk coefficient; S3, in response to the detection that the feasible value set corresponding to the target parameter node is empty, traverse the predecessor node set in reverse along the parameter dependency graph, calculate the backtracking cost coefficient of each candidate backtracking predecessor node, and determine the minimum backtracking target node based on the backtracking cost coefficient to perform fixed-point backtracking. S4. After all parameter nodes in the parameter dependency graph have been verified, the set of parameter values ​​for the current session is serialized into a task snapshot with a version stamp, and the task snapshot is used as an idempotent key to submit a ticketing request to the backend order service.

[0008] By constructing a directed acyclic graph of parameter dependencies to determine the parameter filling order, parameter value conflicts are predicted in advance and displayed in risk-ordered order. When an empty value is encountered, the backtracking cost is calculated to achieve targeted backtracking. Finally, ticketing requests are submitted based on version-stamped task snapshots and idempotent mechanisms. Overall, parameter conflict detection is brought forward, avoiding the drawbacks of traditional models where problems are only exposed after all parameters are filled in, resulting in a whole session rollback. This significantly shortens the conflict discovery time, reduces repetitive user operations, and improves the stability and anti-duplicate capabilities of ticketing requests through snapshots and idempotent submissions, comprehensively optimizing the efficiency and reliability of self-service ticketing interaction.

[0009] Furthermore, in response to a ticket purchase request, the input content is parsed to extract parameter slots. Based on ticketing business rules, a directed acyclic graph (DAG) parameter dependency graph is constructed for the parameter slots, including: The input content is mapped to the parameter slots, and the parameter slots are divided into basic positioning parameters and constraint parameters. Each parameter slot is used as a graph node, and the feasible region shrinkage of the constraint limit parameters after the basic positioning parameters are determined is used as a constraint relationship to establish directed edges, and finally a parameter dependency graph in the form of a directed acyclic graph is obtained.

[0010] By dividing basic positioning parameters and constraint parameters, and building a parameter dependency graph based on their constraint relationship, the hierarchy and linkage rules of different types of ticket purchase parameters are clarified, making the business constraint relationship between parameters explicit. This lays a structural foundation for subsequent orderly filling and pre-emptive conflict detection, ensuring that the parameter guidance process conforms to the actual business logic of ticketing.

[0011] Furthermore, after determining the guiding filling order based on the topological sorting results, the process also includes: Extract multiple parameters provided at once from the input content, and inject these multiple parameters hierarchically according to the parameter dependency graph; Parameters belonging to the root node are locked directly, and it is determined whether parameters belonging to the intermediate nodes satisfy the condition that the predecessor node has completed the feasible region shrinkage and the value belongs to the feasible region of the predecessor node. If the conditions are met, the parameters of the intermediate node are automatically injected and locked; if the conditions are not met, the parameters of the intermediate node are placed in the queue to be verified.

[0012] By performing layered injection and status determination on multiple parameters input by the user at one time, parameters that meet the dependency rules are automatically locked and parameters that do not meet the conditions are temporarily stored. This not only enables the rapid reuse of information already provided by the user and simplifies the operation steps, but also verifies the legality of parameters in advance, preventing invalid input from entering the subsequent process, thereby improving the efficiency of parameter preprocessing and the adaptability of user input.

[0013] Furthermore, following the guided filling order, a feasible region shrinkage operation is performed layer by layer on the parameter nodes in the parameter dependency graph to obtain a set of feasible values, including: Extract the current value combinations of all confirmed predecessor parameters of the current parameter node to be filled; The current combination of values ​​is used as the query condition to initiate a conditional query request to the backend ticketing service to obtain the set of feasible values ​​for the parameter node under the current constraints.

[0014] Based on the confirmed predecessor parameter combination, the feasible values ​​of the current parameters are obtained by querying the ticket database, and the feasible domain of the parameters is gradually narrowed. Invalid options are filtered based on real-time ticket database data, reducing unreasonable parameter selection from the source, and further exposing parameter conflicts in advance during the single node filling stage.

[0015] Furthermore, the subsequent conflict risk coefficient for each candidate value in the feasible value set is calculated, including: Get the number of available agents corresponding to the candidate value; Get the number of seats required for this ticket purchase; Calculate the ratio of available seats to the number of seats, and use this ratio as the subsequent conflict risk coefficient for candidate values.

[0016] The ratio of available seats to the number of seats required for a ticket purchase is used as a conflict risk coefficient to quantify the probability of subsequent failure of each candidate value. Options are displayed in order of coefficient, and priority is given to pushing options with sufficient remaining tickets and lower risk, effectively guiding users to avoid high conflict options and reducing the probability of subsequent unsolvable parameters.

[0017] Further, the backtracking cost coefficient of each candidate backtracking predecessor node is calculated, including: The statistical parameter depends on the total number of nodes contained in the subgraph rooted at the candidate backtracking predecessor node in the graph. Query the number of valid alternative values ​​that are still available in the candidate backtracking predecessor node in the current real-time ticket pool, excluding the selected conflicting values; The backtracking cost coefficient of the candidate backtracking predecessor node is obtained by calculating the ratio of the total number of nodes to the number of valid alternative values.

[0018] Furthermore, determining the minimum backtracking target node based on the backtracking cost coefficient to perform fixed-point backtracking includes: Filter out candidate backtracking predecessor nodes with a valid number of alternative values ​​greater than 0; Among the selected candidate backtracking predecessor nodes, the node with the smallest backtracking cost coefficient is selected as the minimum backtracking target node. Present users with targeted guidance prompts and only show the parameter items that need to be reselected, while locking the remaining verified parameter items to complete the point-to-point backtracking.

[0019] Furthermore, the set of parameter values ​​for the current session is serialized into a version-stamped task snapshot, including: Extract the travel date, train number, seat type, passenger ID number hash, and parameter confirmation timestamp of the current session; The extracted information is combined and processed to generate a unique version stamp; The parameter value set is serialized and bound to the version stamp to form a task snapshot with a version stamp.

[0020] Furthermore, the task snapshot is used as an idempotent key to submit a ticketing request to the backend order service, including: Persist the task snapshot to the terminal's local storage; When submitting a ticketing request to the backend order service, include the version stamp of the task snapshot as an idempotent key; Receive the initial ticketing result returned directly by the backend order service based on the same idempotent key.

[0021] Furthermore, following the guided filling order, a feasible region shrinkage operation is performed layer by layer on the parameter nodes in the parameter dependency graph to obtain a set of feasible values, including: Identify multiple parameter nodes in the parameter dependency graph that are at the same topological level and have no mutual dependencies. The feasible domain query requests for multiple parameter nodes are submitted to the backend ticketing service in an asynchronous and concurrent manner to obtain the set of feasible values ​​corresponding to each parameter node.

[0022] The beneficial effects are: by combining task snapshot persistence with an idempotent submission mechanism, this invention enables the terminal to recover to the verification state before the interruption without loss in the event of network jitter or payment interruption, while preventing duplicate ticketing caused by network retries. This improves the reliability of the terminal in complex network environments, ensures the continuity and accuracy of ticketing transactions, and optimizes the efficiency of ticketing operations in public places. Attached Figure Description

[0023] Figure 1 A flowchart for an automated task guidance process for self-service ticketing terminals.

[0024] Figure 2 This is a comparison chart of the conflict exposure time point distribution between the conflict pre-sensing method and the existing linear state machine method. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] An embodiment of the automated task guidance processing method for self-service ticketing terminals provided by the present invention: like Figure 1 As shown, the automated task guidance method for self-service ticketing terminals includes the following steps: S1, parse the ticket purchase request to construct a parameter dependency graph.

[0027] In an optional embodiment, in response to a user initiating a ticket purchase request at a self-service ticketing terminal, the system parses the input content to extract parameter slots. The input content includes touchscreen selection sequences, voice description text, and pre-filled information via QR code scanning. The system maps the input content uniformly to the parameter slot level before performing subsequent processing to ensure consistent processing paths for different input methods in the subsequent graph construction stage. Parameter slots are categorized into basic positioning parameters and constraint parameters based on semantic type. Basic positioning parameters include departure point, destination, travel date, and train or flight number identifier; constraint parameters include seat type, number of passengers, adjacent seat requirements, and discount eligibility type. The distinction between the two types of parameters lies in the fact that basic positioning parameters directly determine the retrieval scope of the ticket pool, while constraint parameters only provide the prerequisite for feasible domain shrinkage after the basic positioning parameters are determined.

[0028] After extracting the parameter slots, the system constructs a directed acyclic graph (DAG) of parameter dependencies based on ticketing rules. Each node in the graph represents a parameter slot, and directed edges represent constraints that determine the feasible region of subsequent parameters only after the preceding parameters are determined. Specifically, the train or schedule node serves as the root node of the graph, triggering the contraction of the feasible region for seat type nodes; the determination of seat type nodes further triggers the contraction of the feasible region for passenger numbers and adjacent seat requirements nodes. After the dependency graph is constructed, the system uses topological sorting to determine the order in which subsequent parameters are filled, ensuring that each parameter option presented to the user has been filtered for feasible regions based on the preceding parameters, avoiding presenting all candidate options to the user for self-selection.

[0029] Furthermore, for situations where some users provide multiple parameters at once during the initial input phase, such as a voice description like "I need two adjacent business class seats on the high-speed train from Hangzhou to Shanghai tomorrow afternoon," the system injects the extracted parameters hierarchically according to the dependency graph: parameters belonging to the root node are directly locked; for parameters belonging to intermediate nodes, the formal confirmation condition is that the predecessor node has completed feasible region shrinking, and the value provided by the user belongs to a member of the feasible region of that predecessor node. If this condition is met, the intermediate node parameter is automatically injected and locked; otherwise, the parameter is placed in the verification queue, and after the predecessor node completes feasible region shrinking, the subsequent fixed-point backtracking process is triggered to clearly inform the user of the conflict reason and make targeted corrections, avoiding directly rejecting the user's initial input.

[0030] By modeling the ticket purchase parameters as a dependency graph in the form of a directed acyclic graph and determining the guiding filling order according to the topology, the system can establish explicit constraint relationships between parameters during the parameter collection phase. This eliminates the defects of the linear sequential state machine mode, where each parameter slot is isolated from each other and cross-parameter conflicts can only be exposed during the submission phase.

[0031] S2 performs feasible region shrinking and sorts the candidate values ​​for display.

[0032] In an optional embodiment, after the dependency graph is established, the system performs feasible region shrinkage operations on the parameter nodes in the parameter dependency graph layer by layer according to the guided filling order. For the parameter node to be filled, the system first confirms that the required number of seats is not less than 1, and then sends a conditional query request to the backend ticketing service. The query condition is the current value combination of all confirmed predecessor parameters of the node, and the query result is the set of feasible values ​​of the parameter node to be filled under the current constraints. This conditional filtering operation belongs to the existing database conditional retrieval logic.

[0033] Furthermore, after the feasible value set is returned, the system processes each candidate value in the set. Calculate the risk coefficient of subsequent conflict The candidates are sorted according to this coefficient before being pushed to the terminal interface. The relationship is as follows:

[0034] in For candidate values The current number of available seats is returned by the real-time ticket database; The number of seats required for this ticket purchase by the user has been confirmed during the parameter extraction stage. A higher value indicates that the candidate has a sufficient number of remaining seats in the current competitive situation, and the probability of it being rejected by subsequent operations is lower; a lower value indicates that the remaining seats for the candidate are close to or even lower than the required number, and the risk of the feasible field being empty in the subsequent parameter filling stage is higher after the user selects it. The system sorts the candidates in the set according to... The options are displayed to the user in descending order, prioritizing those with more robust feasibility.

[0035] Then, when When the system detects that the number of remaining seats is lower than the required number of seats, it adds a "Limited Seats" label next to the displayed item to remind the user to choose carefully. If the set of feasible values ​​is empty, the system determines that there are no feasible solutions for the parameter node to be filled under the current combination of predecessor parameter values, and immediately triggers a fixed-point backtracking process to avoid exposing conflicts at the submission stage after the user has completed filling in all subsequent parameters.

[0036] It should be noted that the feasible region shrinkage operation is executed asynchronously and concurrently. For multiple parameter nodes in the dependency graph that are at the same topological level and have no mutual dependencies, feasible region query requests are submitted concurrently to the ticketing service to reduce the perceived latency for users. Those skilled in the art can select different concurrency limits and timeout fallback strategies based on the actual concurrency capacity of the ticketing service and the terminal network bandwidth.

[0037] By introducing a subsequent conflict risk coefficient By sorting and displaying candidate options, the system proactively places options with sufficient remaining seats and low probability of failure within the user's priority field of view. This guides users to avoid high-risk selection paths from the candidate option presentation stage, reducing the probability of subsequent parameter nodes having empty feasible domains from the source.

[0038] S3 performs fixed-point backtracking based on the backtracking cost coefficient.

[0039] In an optional embodiment, in response to detecting that the feasible value set corresponding to the target parameter node is empty, the system initiates a fixed-point backtracking process. The system starts from the conflicting node in the dependency graph and traverses the predecessor node set backward along the directed edges, backtracking for each candidate predecessor node with a valid alternative value greater than 0. Calculate the backtracking cost coefficient The relation is:

[0040] in For the dependency map The total number of nodes contained in the subgraph of the root, i.e., if reset... The total number of downstream nodes that need to be re-verified is directly counted from the graph structure; For the current real-time ticket pool The number of valid alternative values ​​available besides the selected conflicting values ​​is directly returned by the vote count condition query. If a candidate backtracks to its predecessor node... This indicates that there are currently no alternative values, and the backtracking pointer continues to propagate up the graph to the previous node until a value is found. Until the node is reached. The system selects. The corresponding predecessor node is used as the minimum backtracking target node. When multiple minimum values ​​exist, the system prioritizes selecting the minimum value. The smallest node ensures the narrowest possible coverage area. Use it as a secondary sorting key to ensure that the most alternative options are available.

[0041] Next, after determining the minimum backtracking target node, the system presents a targeted guidance prompt to the user, clearly explaining the specific reason for the current conflict. For example, the prompt could be "No adjacent business class tickets available for the selected train. Please select a different train or class of seating." Only the parameters that need to be reselected are displayed; the remaining verified parameters remain locked on the interface, and the user does not need to perform any re-operation on these parameters. After the user completes the targeted modification, the system uses the modified parameter values ​​as input and only re-executes feasible region shrinkage on the affected downstream nodes. Parameter nodes not affected do not need to be re-verified.

[0042] By introducing a backtracking cost coefficient, the conflict backtracking operation is accurately located to the predecessor node with the narrowest impact and the most alternatives, and the remaining verified parameters are retained in a locked state. The effective refill operation volume of users in the conflict scenario is positively correlated with the actual impact range of the conflict, eliminating the operation loss of clearing the entire session due to a single parameter conflict.

[0043] S4, serialize the task snapshot and submit the ticketing request.

[0044] In an optional embodiment, after all parameter nodes in the parameter dependency graph have been verified, the system serializes the parameter value set of the current session into a version-stamped task snapshot and persists it to the terminal's local storage. Specifically, the system extracts the travel date, train number identifier, seat type, passenger ID number hash value, and parameter confirmation timestamp of the current session; it then performs comprehensive concatenation processing on the extracted information to generate a unique version stamp; and finally, it serializes and binds the parameter value set with the version stamp to form a version-stamped task snapshot. The persistent task snapshot serves two purposes: first, if the session is interrupted due to terminal network jitter or payment timeout when the user enters the payment process, the system automatically loads the snapshot and restores the payment confirmation page after the user reactivates the terminal, eliminating the need to re-enter parameters; second, the system uses the task snapshot as an idempotent key to submit a ticketing request to the backend order service.

[0045] Furthermore, when submitting a ticketing request to the backend order service, the system carries the version stamp of the task snapshot as an idempotent key; it receives the first ticketing result directly returned by the backend order service based on the same idempotent key, preventing duplicate ticketing caused by network retries. For the extremely low-probability scenario of inventory competition occurring during the time window from task snapshot generation to submission after order submission—that is, when multiple terminals compete for last-minute tickets—the system writes the specific conflict parameters returned by the backend back to the corresponding node in the dependency graph. This conflicting node effectively replaces the state with a value of 0, triggering the fixed-point backtracking pointer to propagate to the upper-level predecessor node. Since this processing path and the fixed-point backtracking process reuse the same backtracking cost calculation entry point, the system displays a targeted guidance prompt to the user that is completely consistent with ordinary parameter conflicts. The guidance logic remains completely consistent between the submission and guidance phases.

[0046] It should be noted that the local persistence methods for task snapshots include encrypting and writing to the terminal's local database or serializing them into encrypted files and storing them in an isolated sandbox directory. After the order is successfully submitted, the system clears the local persistent snapshot to free up storage space and eliminate the risk of residual data.

[0047] In this way, by serializing the set of parameter values ​​into a task snapshot with a version stamp, and using the task snapshot as an idempotent key to submit a ticketing request to the backend order service, the terminal can recover to the verification state before the interruption without loss in the event of network jitter or payment interruption. At the same time, the processing path of backend inventory competition conflict is uniformly merged into the fixed-point backtracking process, ensuring the consistency of the entire link guidance logic from parameter guidance to order submission and the reliability of business.

[0048] like Figure 2As shown, the horizontal axis represents the progress percentage of the task flow, divided into three functional segments by four scales: task start, end of the guidance phase, end of the verification phase, and end of the submission phase. The vertical axis represents the distribution of session samples, without quantitative scales, only indicating the discrete distribution of samples at each progress position. Three different fill patterns are used to distinguish the parameter guidance phase, parameter verification phase, and submission / ticketing phase; two vertical dashed lines mark the phase boundaries. An "×" indicates the location of conflict exposure for each session sample under the existing linear state machine method, concentrated in the interval from the end of the verification phase to the end of the submission phase; a hollow circle "○" indicates the location of conflict exposure for each session sample under the method of this invention, concentrated in the interval from the parameter guidance phase to the parameter verification phase. It can be observed that the two sets of sample points exhibit a clear spatial separation on the process progress axis, indicating that the method of this invention moves the conflict detection timing forward to the earlier stage of the process.

[0049] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for automating task guidance in self-service ticketing terminals, characterized in that: Includes the following steps: S1 responds to the ticket purchase request by parsing the input content to extract parameter slots, constructs a parameter dependency graph in the form of a directed acyclic graph for the parameter slots according to the ticketing business rules, and determines the filling order based on the topological sorting result; S2, perform feasible region shrinkage operation on the parameter nodes in the parameter dependency graph layer by layer according to the guided filling order to obtain a feasible value set, calculate the subsequent conflict risk coefficient of each candidate value in the feasible value set, and sort and display the candidate values ​​according to the subsequent conflict risk coefficient; S3, in response to the detection that the feasible value set corresponding to the target parameter node is empty, traverse the predecessor node set in reverse along the parameter dependency graph, calculate the backtracking cost coefficient of each candidate backtracking predecessor node, and determine the minimum backtracking target node based on the backtracking cost coefficient to perform fixed-point backtracking. S4. After all parameter nodes in the parameter dependency graph have been verified, the set of parameter values ​​for the current session is serialized into a task snapshot with a version stamp, and the task snapshot is used as an idempotent key to submit a ticketing request to the backend order service.

2. The automated task guidance processing method for self-service ticketing terminals according to claim 1, characterized in that, In response to a ticket purchase request, the system parses the input content to extract parameter slots and constructs a directed acyclic graph (DAG) for these slots based on ticketing business rules. This includes: The input content is mapped to the parameter slots, and the parameter slots are divided into basic positioning parameters and constraint parameters. Each parameter slot is used as a graph node, and the feasible region shrinkage of the constraint limit parameters after the basic positioning parameters are determined is used as a constraint relationship to establish directed edges, and finally a parameter dependency graph in the form of a directed acyclic graph is obtained.

3. The automated task guidance processing method for self-service ticketing terminals according to claim 1, characterized in that, After determining the guiding fill order based on the topological sorting results, the following is also included: Extract multiple parameters provided at once from the input content, and inject these multiple parameters hierarchically according to the parameter dependency graph; Parameters belonging to the root node are locked directly, and it is determined whether parameters belonging to the intermediate nodes satisfy the condition that the predecessor node has completed the feasible region shrinkage and the value belongs to the feasible region of the predecessor node. If the conditions are met, the parameters of the intermediate node are automatically injected and locked; if the conditions are not met, the parameters of the intermediate node are placed in the queue to be verified.

4. The automated task guidance processing method for self-service ticketing terminals according to claim 1, characterized in that, Following the guided filling order, perform feasible region shrinkage operations layer by layer on the parameter nodes in the parameter dependency graph to obtain a set of feasible values, including: Extract the current value combinations of all confirmed predecessor parameters of the current parameter node to be filled; The current combination of values ​​is used as the query condition to initiate a conditional query request to the backend ticketing service to obtain the set of feasible values ​​for the parameter node under the current constraints.

5. The automated task guidance processing method for self-service ticketing terminals according to claim 1, characterized in that, Calculate the subsequent conflict risk coefficient for each candidate value in the feasible value set, including: Get the number of available agents corresponding to the candidate value; Get the number of seats required for this ticket purchase; Calculate the ratio of available seats to the number of seats, and use this ratio as the subsequent conflict risk coefficient for candidate values.

6. The self-service ticketing terminal task automation guidance processing method according to claim 1, characterized in that, Calculate the backtracking cost coefficient for each candidate backtracking predecessor node, including: The statistical parameter depends on the total number of nodes contained in the subgraph rooted at the candidate backtracking predecessor node in the graph. Query the number of valid alternative values ​​that are still available in the candidate backtracking predecessor node in the current real-time ticket pool, excluding the selected conflicting values; The backtracking cost coefficient of the candidate backtracking predecessor node is obtained by calculating the ratio of the total number of nodes to the number of valid alternative values.

7. The automated task guidance processing method for self-service ticketing terminals according to claim 1, characterized in that, Determining the minimum backtracking target node based on the backtracking cost coefficient to perform fixed-point backtracking includes: Filter out candidate backtracking predecessor nodes with a valid number of alternative values ​​greater than 0; Among the selected candidate backtracking predecessor nodes, the node with the smallest backtracking cost coefficient is selected as the minimum backtracking target node. Present users with targeted guidance prompts and only show the parameter items that need to be reselected, while locking the remaining verified parameter items to complete the point-to-point backtracking.

8. The automated task guidance processing method for self-service ticketing terminals according to claim 1, characterized in that, Serialize the set of parameter values ​​for the current session into a version-stamped task snapshot, including: Extract the travel date, train number, seat type, passenger ID number hash, and parameter confirmation timestamp of the current session; The extracted information is combined and processed to generate a unique version stamp; The parameter value set is serialized and bound to the version stamp to form a task snapshot with a version stamp.

9. The automated task guidance processing method for self-service ticketing terminals according to claim 1, characterized in that, Submit a ticketing request to the backend order service using the task snapshot as an idempotent key, including: Persist the task snapshot to the terminal's local storage; When submitting a ticketing request to the backend order service, include the version stamp of the task snapshot as an idempotent key; Receive the initial ticketing result returned directly by the backend order service based on the same idempotent key.

10. The self-service ticketing terminal task automation guidance processing method according to claim 1, characterized in that, Following the guided filling order, perform feasible region shrinkage operations layer by layer on the parameter nodes in the parameter dependency graph to obtain a set of feasible values, including: Identify multiple parameter nodes in the parameter dependency graph that are at the same topological level and have no mutual dependencies. The feasible domain query requests for multiple parameter nodes are submitted to the backend ticketing service in an asynchronous and concurrent manner to obtain the set of feasible values ​​corresponding to each parameter node.

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