Intelligent government affair service platform and data processing method applied by same

Abstract

The invention discloses an intelligent government affair service platform and a data processing method applied by the intelligent government affair service platform, and relates to the technical field of government affair service management, and the method comprises a public configuration module which is used for carrying out hierarchical configuration on system service capability according to a configuration instruction, and the hierarchical configuration comprises capability application management configuration, public template configuration and service model configuration; the service model configuration comprises a service overall planning model and a service implementation model; the reservation rule engine module comprises multi-level reservation rules of a hall reservation rule, a special area reservation rule and an item reservation rule, rule parameters can be dynamically adjusted, and the multi-level reservation rules comprise a reservation time period, a government affair service number allocation strategy and a conflict detection mechanism; the business handling module is used for realizing automatic material verification and document generation in a certificate-free business scene; and carrying out data interaction with an external system through the capability application management module, and carrying out system service capability authorization. The service efficiency of government affair services is improved, and the government affair handling experience of the masses is improved.

Description

Technical Field

[0001] This application relates to the technical field of government service management, and in particular to a data processing method for an intelligent government service platform and its applications. Background Art

[0002] Currently, there are problems in the government service system where the service model configuration is disconnected from the business requirements: on the one hand, the functional modules are solidified and cannot be hierarchically adapted to the differentiated authorization requirements at different levels (such as municipal / district levels); on the other hand, for the business appointment scenario that requires making an appointment for the government service number source to handle government services, the number source appointment rules for government services lack a conflict detection mechanism, and it is easy to cause allocation errors due to overlapping multi-level rules. These problems lead to low efficiency of government services and urgent improvement is needed. Summary of the Invention

[0003] In order to improve the efficiency of government services and optimize the experience of the masses in handling affairs, this application provides a data processing method for an intelligent government service platform and its applications.

[0004] In the first aspect, the invention object of this application is achieved by adopting the following technical solutions: An intelligent government service platform, comprising: A public configuration module, used to hierarchically configure the system service capabilities according to the received configuration instructions. The hierarchical configuration includes capability application management configuration, public template configuration, and service model configuration. The service model configuration includes a service overall planning model and a service implementation model; A reservation rule engine module, including multi-level reservation rules for hall reservation rules, zone reservation rules, and item reservation rules. The rule parameters of the multi-level reservation rules are dynamically adjusted based on the reservation status. The multi-level reservation rules include reservation time periods, government service number release strategies, and conflict detection mechanisms; A business handling module, integrated with an electronic certificate library and a digital signature verification unit to achieve automated material verification and document generation in the scenario of handling business without certificates; The platform conducts government service data interaction with external systems through a capability application management module and authorizes the system service capabilities based on the received user login request.

[0005] By adopting the above technical solutions, the appointment rule engine module supports dynamic adjustment of multi-level appointment rules. The present invention solves the problem of rigid service models through a hierarchical configuration architecture. The appointment rule engine module adopts a dynamic rule engine to optimize the fairness of number source allocation. The business handling module can achieve automatic verification in the scenario of handling affairs without certificates; the hierarchical configuration module of the present application supports city-level / district-level differential permission settings, and realizes dynamic adaptation through the overall planning model and the implementation model, which is beneficial to reducing the number source conflict rate and improving service efficiency; the multi-level appointment rule engine is built with a conflict detection mechanism, combined with a dynamic priority strategy and encrypted number source management, to improve the allocation accuracy; at the same time, the business handling module integrates electronic certificate and signature verification functions, realizes automatic verification of materials in the scenario of handling affairs without certificates, reduces manual intervention, and is beneficial to improving the public's experience in handling government affairs.

[0006] In a preferred example of the present application: The hierarchical configuration includes: When configuring the overall planning model, configure government service content, process links, and intelligent service declaration rules based on a preset standardized matter model; When configuring the implementation model, obtain service links corresponding to the government service content or the process links based on the overall planning model, bind link authorized personnel accounts, document templates, and handling channels based on the service links, and configure audit nodes; The public configuration module is connected to a visual configuration terminal. The visual configuration terminal receives configuration instructions for configuring the overall planning model and the implementation model, and synchronizes based on the configuration results to the business handling module for performance detection.

[0007] By adopting the above technical solutions, the overall planning model directly applies a standardized service template like a "template library" (such as uniformly filling out forms and specifying handling steps), saving the time of repeated configuration and ensuring the unified specification of the city-wide / district-wide government service process; the implementation model: flexibly binds specific executors, document templates, and handling channels on the basis of the template (such as a certain matter must be submitted through the APP), and can also automatically set audit nodes to achieve "one size fits all" refined services to meet the needs of different scenarios.

[0008] In a preferred example of the present application: The appointment rule engine module performs the following operations: When detecting a conflict in multi-level appointment rules, dynamically adjust the number source allocation based on the number release template management unit according to a preset priority strategy; Realize encrypted storage and timed release of number sources in batches through the number release template management unit; The rule parameters of the multi-level appointment rules include the weight coefficients of the alternative rules and the blacklist update frequency of each appointment rule.

[0009] By adopting the above technical solutions, in terms of conflict handling, when the appointment rule engine encounters duplicate number releases or scalpers grabbing numbers, it automatically adjusts the number source allocation (for example, giving priority to the elderly, the weak, the sick, and the disabled), reducing manual intervention. In terms of number source management, the number sources are stored in batches and encrypted (for example, releasing numbers 3 times a day), and released regularly to prevent being snapped up instantly. It can also dynamically adjust the rules according to real-time needs (for example, increasing the number sources during holidays, and the specific dynamic adjustment parameters can be defined according to your own needs), making the number source allocation more fair and the public appointment experience smoother.

[0010] In a preferred example of this application: Configuring government service content, process links, and intelligent service declaration rules based on a preset standardized matter model includes: Associating an electronic form of government service content based on a preset standardized matter model, including: when selecting an electronic form, making an associated selection based on retrieval fields such as form name, administrative division, or competent department; after selecting the target form, the system loads the form fields and performs field-level mapping with the acceptance conditions and handling materials in the government service content; When associating handling materials, query the electronic certificate library on the selection interface, and query and filter the target electronic certificates by certificate name, administrative division, or competent department; When associating handling results, generate an electronic certificate template of the result materials based on the result generation instruction, and configure the issuance rules including the issuing department and the service validity period.

[0011] By adopting the above technical solutions, the electronic form is linked with the electronic certificate. By selecting a form, the electronic certificate can be automatically matched (for example, when selecting "business license", the enterprise name and legal person information are automatically brought out), reducing manual filling errors; when submitting materials, it automatically compares with the electronic certificate library (for example, real-time verification of ID card information with the public security system), avoiding duplicate submission of materials; after the matter or business is completed, an electronic certificate is automatically generated (for example, an electronic approval document with the issuing department and validity period), which can be directly downloaded and used, helping to improve the handling speed and reduce the amount of materials submitted.

[0012] In a preferred example of this application: In the overall planning model, the handling channels include offline halls, online APPs, or self-service terminals; the handling methods of the handling channels include unified channels and differentiated channels: In the overall planning model, all service handling items of the unified handling channel share the channel configuration; the differentiated channel configures a corresponding handling channel for each service handling item, and the handling channel is associated with the priority of the channel matters, and matters are handled based on the priority of the channel matters.

[0013] By adopting the above technical solutions, the channels of the overall planning model are configured differentially. Through a unified channel, all matters share the same set of online entrances (such as the city-wide handling APP), saving development and maintenance costs; the differential channels are configured separately for special matters (such as the offline handling of social security cards must go to the designated hall), and can also be automatically diverted according to the urgency (such as the priority handling of social security card loss reporting); this application not only reduces the system complexity but also can accurately match the needs of the masses, avoiding resource waste caused by "one-size-fits-all".

[0014] In the second aspect, the invention object of this application is achieved by adopting the following technical solutions: A data processing method applied to an intelligent government service platform, including: Obtain a configuration instruction, and perform hierarchical configuration on the system service capabilities according to the configuration instruction. The hierarchical configuration includes capability application management configuration, public template configuration, and service model configuration, where the service model configuration includes a service overall planning model and a service implementation model; Based on the appointment rule engine module, execute multi-level appointment rules. The multi-level appointment rules include hall appointment rules, zone appointment rules, and matter appointment rules, where the parameters of the multi-level appointment rules are dynamically adjusted based on the appointment status, and the multi-level appointment rules include appointment time periods, government service number release strategies, and conflict detection mechanisms; Integrate the electronic certificate library and the digital signature verification unit through the business handling module to achieve automatic material verification and document generation in the scenario of handling business without certificates; Perform government service data interaction with an external system through the capability application management module, and authorize the system service capabilities based on the received user login request.

[0015] By adopting the above technical solutions, the hierarchical configuration configures government services like "building blocks". For example, first select a general template (fill in the form uniformly), and then fine-tune specific links (such as specifying that a certain matter must be handled online), which is time-saving, labor-saving and flexible; the appointment rule engine can dynamically adjust the number of released numbers according to the real-time traffic flow (such as releasing more numbers on weekdays and fewer numbers on weekends), and can also automatically detect conflicts (such as the same person making repeated appointments for different windows), reducing scalpers from grabbing numbers; the business handling module can automatically verify materials when handling business without certificates (such as swiping the face to retrieve the electronic version of the user's household register) and directly generate standard documents (such as automatically filling out the application form), with almost "zero operation" for the masses, more flexible service configuration and fairer appointments.

[0016] In a preferred example of this application: the service overall planning model is used to overall plan the resource allocation and process coordination between different government matters, and the service implementation model is used to define the service path, approval nodes, and service interfaces of specific matters; The dynamic adjustment of the reservation rules includes: optimizing the division of reservation time periods and the ticket release frequency according to the real-time reservation number, resource usage conditions, and historical reservation data; The conflict detection mechanism is used to identify time conflicts, personnel conflicts, and resource conflicts during the reservation process, and trigger a warning or automatically reallocate when a conflict is detected.

[0017] By adopting the above technical solutions, the overall planning model allocates resources like "traffic dispatching" (for example, when there are many people queuing for matter A, it automatically diverts them to the handling channel for matter B), avoiding resource waste; the dynamic reservation adjustment optimizes the ticket release time according to historical data (for example, if it is found that there are fewer people on Wednesday mornings, more tickets are released), enhancing the public experience; the conflict detection is used to automatically detect situations such as "the same person making reservations for two windows simultaneously" or "material conflicts", and immediately reminds to re-reserve, reducing manual error correction.

[0018] In a preferred example of the present application: The method further includes: Based on the historical business data set of the intelligent government service platform, obtaining the historical business operation data and business logic association rules during the operation of multiple government affairs processes; the business logic association rules include multiple working stage intervals corresponding to different approval complexities; the government affairs processes are associated with unique business identification codes; Obtaining the historical approval data sets of each government affairs process based on the business identification code, and training and optimizing based on the approval complexity in a preset initial data processing model to obtain an intelligent decision-making model; Based on the historical business data set of the intelligent government service platform, calculating and determining the associated business factors between each government affairs process to obtain the business factor correlation coefficients of all government affairs processes; In the intelligent decision-making model, according to the business factor correlation coefficients of all government affairs processes and the approval parameter adjustment strategy corresponding to the historical approval data set, determining the approval time target values of each government affairs process in each working stage interval, and generating an optimal data processing strategy; Dynamically optimizing and regulating the approval time of each government affairs process of the intelligent government service platform according to the optimal data processing strategy.

[0019] By adopting the above technical solutions, a data processing method driven by historical data + intelligent decision-making model + dynamic optimization is provided. It automatically identifies "simple matters" (such as being completed in 3 minutes with complete materials) and "complex matters" (such as requiring cross-department verification) through approval complexity grading, and differentially allocates resources; the dynamic training model learns historical data like an "AI teacher" (for example, if it is found that a certain link always times out, it automatically adjusts the strategy), and becomes more accurate with use. The time target value is used to set a "shortest completion time" for each link (for example, the initial review of materials must be completed within 1 hour), and an automatic warning is triggered when it times out, speeding up the overall process, thus achieving the effect of doubling the approval efficiency and reducing the timeout problem.

[0020] In a preferred example of this application: obtaining historical business operation data and business logic association rules during the operation of multiple government affairs processes based on the historical business data set of the intelligent government affairs service platform, including: Obtaining the business handling records and corresponding manual intervention frequency data of each government affairs process during the historical service cycle based on the historical business data set of the intelligent government affairs service platform; Creating multiple historical service time intervals according to the business handling records and manual intervention frequency data; Dividing the business handling records and manual intervention frequency data of each government affairs process based on the business identification code according to multiple historical service time intervals, and correspondingly obtaining multiple historical business operation data of each government affairs process; Determining the differentiated business logic association rules of each government affairs process correspondingly according to the manual intervention frequency data and the preset logical rule judgment conditions in multiple historical business operation data.

[0021] By adopting the above technical solutions, differentiated rules for manual intervention marking and historical time interval division are formulated: the problem of "always getting stuck at a certain link" (such as a certain material being repeatedly returned for modification) is automatically discovered through manual intervention marking, and the process is optimized accordingly; the historical time interval division is optimized in stages according to "busy hours / idle hours" (such as reducing the number of complex matters released during the lunch break), and resources are reasonably allocated.

[0022] In a preferred example of this application: obtaining the historical approval data set of each government affairs process based on the business identification code, and training and optimizing it based on the approval complexity in a preset initial data processing model to obtain an intelligent decision-making model, including: Extracting the approval stage feature data of each government affairs process according to the business identification code, including the duration of approval links, the material transfer path, and the cross-departmental collaboration time-consuming; Constructing a multi-dimensional approval complexity evaluation index according to the timeout nodes and repeated submission nodes in the approval stage feature data; Inputting the historical approval data set marked with the approval complexity level into the initial data processing model, and using the dynamic weight adjustment algorithm to iteratively train the initial data processing model, so that the data processing model learns the approval time optimization rules in different complexity scenarios; Based on the output of the trained data processing model, the time threshold parameters of each approval link are generated, and combined with the cross-departmental collaboration efficiency constraint conditions, an intelligent decision-making model adapted to the current government affairs process is generated.

[0023] By adopting the above technical solutions, analyze based on the approval stage characteristics and locate abnormal nodes to automatically identify the "bottleneck" links (such as the total overtime of cross-departmental collaboration), and specifically break through the blockages; the dynamic weight algorithm adjusts the strategy according to the real-time situation (such as giving priority to handling urgent matters when there are a large number of sudden applications) to avoid system crashes; the time limit threshold parameter is used to set a "passing line" for each step (such as the material upload must be completed within half an hour), and manual intervention is automatically triggered when the time limit is exceeded.

[0024] In summary, this application includes at least one of the following beneficial technical effects: 1. Hierarchical configuration is like "Lego bricks": a general template serves as the base, and it can be freely combined as needed (such as adding a rule of "door-to-door handling" for special matters in a certain street); the dynamic appointment rule is like an "intelligent traffic signal": adjust the green light duration (the number of released numbers) according to the real-time traffic flow (the number of appointment people); the automation of handling without certificates is like an "AI secretary": automatically retrieve the user's household register and generate an application form, and the masses only need to "click"; the data interaction platform is like the "government affairs central nervous system", which is used to connect the data of various departments and automatically "pass the review" during authorization (such as when the social security bureau calls the data of the tax bureau, the user needs to nod in agreement). 2. The differential business logic association rules are more in line with the actual situation, the pressure during peak periods is reduced, and the experience of the masses is more stable. 3. The process bottlenecks are reduced, the handling of complex matters is smoother, and the masses run less errands. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 is a framework diagram of an intelligent government service platform in an embodiment of this application; Figure 2 is an example diagram of the configuration and application management of the public configuration module in an intelligent government service platform in an embodiment of this application; Figure 3 is an example diagram of the configuration process template of the public configuration module in an intelligent government service platform in an embodiment of this application; Figure 4 is an example diagram of the configuration of the configuration overall planning model of the hierarchical configuration in an intelligent government service platform in an embodiment of this application; Figure 5 is an example diagram of the configuration of the configuration implementation model of the hierarchical configuration in an intelligent government service platform in an embodiment of this application; Figure 6 is a flowchart of a data processing method applied to an intelligent government service platform in an embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] The following further describes this application in detail with reference to the accompanying drawings.

[0027] In one embodiment, asFigure 1 As shown in the figure, the present application discloses an intelligent government service platform. The intelligent government service platform includes a public configuration module, a reservation rule engine module, a business handling module, and a capability application management module. The public configuration module is used to hierarchically configure the system service capabilities according to the received configuration instructions. The hierarchical configuration includes capability application management configuration, public template configuration, and service model configuration. The service model configuration includes a service overall planning model and a service implementation model.

[0028] As Figures 2 to 5 shown, the hierarchical configuration of the public configuration module includes: As Figure 4 shown, when configuring the overall planning model, the government service content, process links, and intelligent service declaration rules are configured based on a preset standardized matter model. Specifically, the electronic form of the government service content is associated based on the preset standardized matter model, including: when selecting the electronic form, the association selection is performed based on the retrieval fields of the form name, administrative division, or competent department; after the target form is selected, the system loads the form fields and performs field-level mapping with the acceptance conditions and handling materials in the government service content; when associating the handling materials, the electronic certificate library is queried on the selection interface, and the target electronic certificate is queried and filtered by the certificate name, administrative division, or competent department; when associating the handling results, the electronic certificate template of the result material is generated based on the result generation instruction, and the issuance rules including the issuing department and the handling validity period are configured. In the overall planning model, the handling channels include the offline hall, the online APP, or the self-service terminal; the handling methods of the handling channels include the unified channel and the differentiated channel: in the overall planning model, all service handling items of the unified handling channel share the channel configuration; the differentiated channel configures the corresponding handling channel for each service handling item, and the handling channel is associated with the channel item priority, and the matter handling is performed based on the channel item priority.

[0029] As Figure 5 shown, when configuring the implementation model, the service links corresponding to the government service content or process links are obtained based on the overall planning model, and the link authorized personnel accounts, document templates, and handling channels are bound based on the service links, and the review nodes are configured. The public configuration module is connected to the visual configuration terminal. The visual configuration terminal receives the configuration instructions for configuring the overall planning model and the implementation model, and synchronizes to the business handling module based on the configuration results for efficiency detection.

[0030] The reservation rule engine module includes multi-level reservation rules for lobby reservation rules, zone reservation rules, and item reservation rules. The rule parameters of the multi-level reservation rules are dynamically adjusted based on the reservation status. The multi-level reservation rules include reservation time periods, government service number release strategies, and conflict detection mechanisms. The operations performed by the reservation rule engine module include: when detecting conflicts in the multi-level reservation rules, dynamically adjusting the number source allocation based on the number release template management unit according to the preset priority strategy. Specifically, the priority strategy includes priority for special groups, priority for historical credit, and priority for urgent services. Among them, special groups are identified by recognizing the identification signs of the elderly, the weak, the sick, and the disabled, historical credit is obtained by querying the user's credit score, and the urgency of the service is determined by judging the urgent level of the item. The number release template management unit stores the numbers in an encrypted manner and releases the number sources at regular intervals.

[0031] The encrypted storage and timed release of number sources in batches are implemented through the number release template management unit. Encrypted storage means that the number source data is encrypted in slices using the AES-256 algorithm, and each number source block is associated with a unique key (such as K1-Kn). Timed release means that through the Quartz timed task framework, the number sources are released according to the following strategy: Obtain the current time of the number release template management unit: By calling the number release system clock module, obtain the current real-time time information as the basic basis for judging whether the resources meet the release conditions.

[0032] Traverse the preset planned batch list: One or more resource batch objects to be processed are maintained in the number release system. Each batch contains at least one encrypted resource item to be released, and each batch is also associated with a preset release time.

[0033] Judge whether the release conditions are met: Compare the current number release system time with the release time set for each batch. If the current time is equal to the release time of the batch, it is determined that the batch has met the release conditions and can enter the subsequent processing flow.

[0034] Execute the resource decryption and release operation: For the batches that meet the release conditions, call the corresponding decryption mechanism to decrypt one or more encrypted resources included in the batch and transfer them to the specified target path or open access interface for users to access or system calls.

[0035] Mark the batch as the completed status: After the resources are successfully released, update the status flag of the batch and mark it as "completed". An example of the dynamic adjustment of the number source is that when it is detected that the reservation volume in a certain time period suddenly increases, the number release template management unit automatically triggers the following process: Step 1: Judge whether the reservation volume in the current time period exceeds the reservation volume threshold; if not, do not enter Step 2 and continue to release the number sources according to the original number source release mechanism; if it exceeds the reservation volume threshold, enter Step 2; Step 2: Activate the emergency number release mechanism: preferentially release the number sources for the next day and compress the release interval of ordinary number sources.

[0036] The number release template management unit executes a dynamic number source allocation and scheduling strategy based on the conflict type detected by the conflict detection. For example, when a time conflict of the number source is detected, the number release template management unit triggers a priority scheduling strategy, rearranges the task execution order according to the preset task priority order, and ensures that high-priority tasks obtain the priority execution right. In the case of detecting a resource conflict, the number release template management unit activates an emergency batch processing mechanism, temporarily allocates extra resources or delays the execution of low-priority tasks to alleviate the resource tension and ensure the smooth execution of critical tasks. The rule parameters of the multi-level reservation rules include the waiting list rule weight coefficients and the blacklist update frequency of each reservation rule.

[0037] The business handling module integrates an electronic certificate library and a digital signature verification unit to achieve automated material verification and document generation in the scenario of handling business without certificates. The business handling module is also associated with a semantic analysis function based on NLP. Specifically, the automated material verification is an electronic certificate verification technology, that is, the user submits the handling materials to the intelligent terminal (i.e., the business handling module), the intelligent terminal queries the electronic certificates in the electronic certificate library, returns the matching certificates to the intelligent terminal, the intelligent terminal extracts the material information of the user's handling materials through OCR technology, and completes the matching of the material application information elements by calling the AI interface of AI_Service. The AI interface supports multi-modal verification, such as OCR text recognition, face biometric comparison, and seal image recognition; returns the structured material application information matching result to the intelligent terminal, and the intelligent terminal feeds back the user information verification to the intelligent terminal in real time through the Verification Service interface to compare and verify the user's handling information. After the user's handling information is verified successfully again, the material verification result is returned to the intelligent terminal, and the user can obtain the application verification result of the handling materials at this time. Among them, the document generation asynchronous queue (Kafka) processes high-concurrency requests. Document generation refers to the dynamic rendering of templates, the adaptability of document templates, and the embedding of electronic seals based on the preset document templates in the implementation model. Among them, the dynamic rendering of templates supports XML / XSLT conversion and can embed dynamic calculation fields. The adaptability of the document template layout means automatically adjusting the layout format according to the content of the user's application materials, and the embedding of electronic seals can comply with the technical specifications of the Electronic Signature Law of the People's Republic of China.

[0038] The platform conducts government service data interaction with external systems through the capability application management module, and authorizes system service capabilities based on the received user login request. System service capability authorization means that after the user's identity authentication is passed, the platform dynamically grants permissions to access government service resources according to its permission configuration. The home page of the capability application management module supports viewing information related to the public configuration module, including service capability overview statistics, to-do tasks (to-do items temporarily stored for submission in the service model and to-do items formed due to standardization changes), entry points for common function modules, message announcement modules, etc.

[0039] In this embodiment, to further illustrate the functions and implementation methods of an intelligent government service platform: as Figures 2 to 5 shown, the configuration of the public configuration module through the capability application management module at the capability application management configuration layer is as follows: Provide capability application authorization management. For example, for configuring queuing service authorization, first synchronize the service list, select the service without configured authorization to enter the details page, configure the capability name and code, and after submission, perform object authorization, select the authorization type and object. After completing the authorization, you can view, modify, or delete.

[0040] The configuration in the public template configuration is as follows: 1. Configure the process template: By adding a new template, filling in the basic information of the template, and submitting after determining the main process link and branch process links. It can be used for reuse when configuring process links for matters (refer to Figure 3 ).

[0041] 2. Configure the personnel authorization template: By adding a new template, filling in the basic information, selecting the link authorization type and authorized personnel, and currently only supports revision after submission.

[0042] 3. Configure the SMS template: By adding a new template, determining after filling in the information according to the template type, and the signature / seal position can be configured.

[0043] 4. Configure the document template: By adding a new template, determining after filling in the information. If electronic signature / seal is required, select and configure the signature position.

[0044] Refer to Figure 4 , the configuration of the overall planning model is as follows: Enter the service model >> Incorporate management >> Incorporate into modeling, perform incorporation operations on the matters that need to be modeled, enter the overall planning service model management >> To-be-processed list, and you can see the list of matters in the to-be-modeled overall planning list that have been incorporated into modeling. Click [New Model] to perform model configuration, including acceptance conditions, business forms, handling materials, handling results, process links, etc. After configuration, you can choose to save temporarily or publish.

[0045] Refer to Figure 5, the configuration of the implementation model is as follows: Enter the service model >> Implementation service model management >> Pending list, click [New model] to enter the model editing page, initialize based on the information of the overall service model, configure the authorized personnel for the configuration link and associated document templates, SMS templates, etc., configure the handling channels, and other information can be modified as needed. After configuration, click Save temporarily or Submit.

[0046] Specifically, the configuration of the hall appointment rules in the appointment rule engine module includes the opening hours of the appointment service, the cut-off appointment time for the appointment period, the maximum personal appointment quantity, the waiting list rule, the blacklist rule, the appointment notice, etc., and new or modified operations can also be performed.

[0047] The special zone appointment rules are similar to the hall appointment rules. The available appointment days, the appointment dimension for handling affairs, the appointment QR code, the cut-off appointment time, the maximum personal appointment quantity, the cancellation rule, the waiting list rule, the blacklist rule, the sorting of matters in the special zone, etc. can be queried and configured. The sub-special zone appointment rules can query and configure the available appointment days, the appointment QR code, the cut-off appointment time, the sorting of matters in the special zone, etc. The matter appointment rules can query the details, including the total matter appointment quantity, the maximum personal appointment quantity, the custom appointment form, the appointment notice, etc., and new or modified operations can also be performed.

[0048] The government service number release strategy includes appointment number source management and template management related to number sources: Appointment number source management includes: The special zone number release rules can query the special zone details, including the special zone information, number release configuration, historical records, etc. Click the appointment handling date to view the number release configuration for that day. New number release configuration: On the number release configuration page, click [New number release configuration], select the applied appointment handling date, the application date type, select the number release configuration template, and configure whether to release numbers in batches and the number and time of each batch of number releases. Modifying the number release configuration includes batch modification or modification and update of the number release configuration for the current date.

[0049] In one embodiment, as Figure 6 shown, a data processing method applied to an intelligent government service platform is provided. This data processing method applied to an intelligent government service platform is applied to the above-mentioned intelligent government service platform, and specifically includes the following steps: S1: Obtain a configuration instruction, and perform hierarchical configuration on the system service capabilities according to the configuration instruction. The hierarchical configuration includes capability application management configuration, public template configuration, and service model configuration. Among them, the service model configuration includes a service overall model and a service implementation model.

[0050] In this embodiment, the capability application management is configured for the authorization management of government service capabilities (such as queuing service, form service); the public template configuration refers to the configuration of highly reusable process / personnel / sms / document templates; the overall model of the service model configuration refers to the municipal adaptation configuration based on provincial standardized matters, and the implementation model is the final execution configuration combined with local channels (online or offline).

[0051] Specifically, the service overall model is used to coordinate the resource allocation and process collaboration among different government affairs matters, and the service implementation model is used to define the service path, approval nodes and service interfaces of specific matters.

[0052] S2: Based on the appointment rule engine module, execute multi-level appointment rules, which include hall appointment rules, zone appointment rules and matter appointment rules. Among them, the parameters of the multi-level appointment rules are dynamically adjusted based on the appointment status, and the multi-level appointment rules include appointment time periods, government service number release strategies and conflict detection mechanisms.

[0053] In this embodiment, the hall appointment rule refers to the global appointment strategy of the offline physical government affairs hall; the zone appointment rule refers to the rules of subdivided business areas (such as "tax zone", "social security zone"); the matter appointment rule refers to the personalized rules of a single government service matter; the dynamic adjustment refers to automatically optimizing the parameters based on indicators such as real-time appointment volume and cancellation rate.

[0054] The dynamic adjustment of the appointment rules includes: optimizing the appointment time period division and number release frequency according to the real-time appointment number, resource usage situation and historical appointment data. The conflict detection mechanism is used to identify time conflicts, personnel conflicts and resource conflicts during the appointment process, and trigger an early warning or automatically reallocate when conflicts are detected.

[0055] S3: Integrate the electronic certificate library and the digital signature verification unit through the business handling module to achieve automated material verification and document generation in the scenario of handling business without certificates.

[0056] In this embodiment, the business handling module integrates the core components of the electronic certificate library and the digital signature service; the automated material verification automatically fills in materials through certificate data comparison; the document generation refers to automatically generating standardized documents based on document templates and verification results.

[0057] S4: Conduct government service data interaction with external systems through the capability application management module, and authorize the system service capabilities based on the received user login request.

[0058] In this embodiment, external systems such as Yue Zheng Yi, the provincial government service network, self-service terminals, etc.; the user login request refers to the identity authentication request initiated through methods such as account password, scanning code, digital certificate, etc.

[0059] Specifically, the Drools rule engine is used to implement dynamic policy calculation, and the microservice architecture splits modules such as appointment management and template configuration into independent services; data transmission is encrypted using HTTPS+AES, and sensitive operations use an operation trace and permission hierarchical approval mechanism.

[0060] In one embodiment, a data processing method applied to an intelligent government service platform further includes: S10: Based on the historical business data set of the intelligent government service platform, obtain the historical business operation data and business logic association rules of multiple government processes during operation; the business logic association rules include multiple work stage intervals corresponding to different approval complexities; the government process is associated with a unique business identification code.

[0061] In this embodiment, the business identification code is a global code (such as UUID) that uniquely identifies the government affairs process and runs through the entire life cycle of the process; the work stage interval is the stage divided according to the complexity of the approval (such as "initial review of materials → expert review → issuance of results"); the business logic association rules refer to the dependency relationship and flow conditions between process nodes (such as "automatically triggering correction when materials are incomplete").

[0062] Specifically, the Apriori algorithm is used to mine association rules between process nodes (such as "submit real estate certificate → automatically trigger real estate verification"); the clustering algorithm is used to divide the work stage intervals (such as defining the "material preparation stage" as a set of nodes that take ≤3 days).

[0063] In this embodiment, step S10 includes: S101: Based on the historical business data set of the intelligent government service platform, obtain the business processing records and corresponding manual intervention frequency data of each government process within the historical service cycle.

[0064] In this embodiment, the service cycle refers to the entire life cycle of a government process from initiation to termination; the business processing record refers to the operation log of each node in the government process (such as acceptance time, processing personnel, and approval results); the frequency of manual intervention refers to the number of operations in the process that require manual intervention (such as supplementary materials, rejection of reconsideration, and special approval).

[0065] Specifically, historical data is extracted from the database or ES log. The fields include process instance ID, node name, such as "material initial review", processing personnel, operation timestamp, and intervention type, such as "correction" and "rejection".

[0066] S102: Create multiple historical service time intervals based on business processing records and manual intervention frequency data.

[0067] In this embodiment, the time interval is an analysis window divided by time granularity (such as by month, by quarter, or by business peak period).

[0068] S103: Based on multiple historical service time intervals, divide the business handling records and manual intervention frequency data of each government affairs process according to the business identification code, and correspondingly obtain multiple historical business operation data of each government affairs process.

[0069] In this embodiment, the multiple historical business operation data are grouped by time interval according to the business identification code.

[0070] S104: According to the manual intervention frequency data and the preset logical rule judgment conditions in the multiple historical business operation data, correspondingly determine the differential business logic association rules of each government affairs process.

[0071] In this embodiment, the logical rule judgment conditions are determined based on the manual intervention frequency threshold, and the manual intervention frequency thresholds for different manual intervention types and different service item types can be defined and set by oneself; the manual intervention frequency threshold refers to the critical value of the number of manual interventions for the preset trigger rule (such as "the number of corrections ≥ 3 times"). The logical rule judgment conditions can be judged based on the causal relationship of the manual intervention frequency (such as "if the correction rate in stage A > 20%, then a review link needs to be added in the next stage").

[0072] Specifically, calculate node-level indicators, such as the correction rate = the number of corrections / the total number of approvals, the average node processing duration, and statistical-level indicators, such as the average process duration = SUM(end time - start time) / the total number of processes. Use the Apriori algorithm to find the co-occurrence frequency of frequent item sets such as (node A, correction) → (node B, rejection), so as to calculate the rules with a confidence level ≥ 80% (such as "node A correction → node B rejection"), and through decision tree classification, predict high-risk nodes, such as based on the process node characteristics of the correction rate, the experience value of the processing personnel, and the material complexity, judge whether to trigger manual intervention, and use the confusion matrix to evaluate the accuracy of the rules.

[0073] S20: Obtain the historical approval data sets of each government affairs process based on the business identification code, and perform training and optimization based on the approval complexity in the preset initial data processing model to obtain an intelligent decision-making model.

[0074] In this embodiment, the initial data processing model is a benchmark model based on historical data (such as a random forest regression model); the approval complexity is an index used to quantify the number of process nodes (such as a simple process ≤ 3 nodes, a complex process ≥ 5 nodes); training and optimization refer to improving the model prediction accuracy through parameter tuning.

[0075] Specifically, step S20 includes: S201: Extract the approval stage feature data of each government affairs process according to the business identification code, including the duration of the approval link, the material transfer path, and the cross-departmental collaboration duration.

[0076] In this embodiment, the duration of the approval process refers to the processing time from the start to the end of a single node (e.g., "preliminary review of materials" takes 2 hours); the material transfer path refers to the transfer track of electronic materials between nodes (e.g., "applicant → window → approval section → deputy leader in charge"); the time-consuming of cross-departmental collaboration refers to the total time-consuming of multi-department collaboration nodes (e.g., "joint inspection by housing construction + environmental protection" takes 1 working day).

[0077] S202: Construct multi-dimensional approval complexity evaluation indicators based on the abnormal node information in the approval stage characteristic data.

[0078] In this embodiment, the abnormal nodes include timeout nodes, repeated submission nodes, and rejection nodes; the multi-dimensional evaluation indicators include quantifying complexity from three dimensions of time, quality, and collaboration. Among them, the time dimension refers to the average processing duration and timeout rate (number of timeout nodes / total number of nodes); the quality dimension refers to the number of corrections and return rate (number of rejection nodes / total number of nodes); the collaboration dimension refers to the proportion of cross-department nodes and the proportion of collaborative time-consuming.

[0079] Specifically, define the threshold rules: Timeout node: link duration > average duration + 2σ (standard deviation) Repeated submission node: the number of submissions of the same material ≥ 3 times.

[0080] The weighted calculation formula for complexity score is: complexity score = × timeout rate + × number of corrections + γ × proportion of cross-departmental collaboration time-consuming; determine the optimal weights through grid search (e.g., = 0.4, = 0.3, γ = 0.3). Set different levels of complexity grades, such as the low-priority score range is 0 - 30 points, the medium-priority level score range is 31 - 70 points; the high-priority level is 71 - 100 points.

[0081] S203: Input the historical approval data set marked with the approval complexity level into the initial data processing model, and use the dynamic weight adjustment algorithm to iteratively train the initial data processing model, so that the data processing model learns the approval time optimization rules in different complexity scenarios.

[0082] In this embodiment, the dynamic weight adjustment algorithm is an online learning algorithm, and the FTRL algorithm is used in this embodiment; the time optimization rule refers to the optimal approval parameters in different complexity scenarios (such as timeout threshold, personnel ratio).

[0083] S204: Output the time limit threshold parameters for each approval link based on the trained data processing model, and generate an intelligent decision-making model adapted to the current government affairs process in combination with the cross-departmental collaboration efficiency constraint conditions.

[0084] In this embodiment, the time limit threshold parameter refers to the maximum processing time allowed for each node (such as "material preliminary review ≤ 2 hours"); the cross-departmental collaboration efficiency constraint refers to the time window for collaboration between departments (such as "joint inspection needs to be completed within 48 hours"); the intelligent decision-making model is a rule engine that combines time limit parameters and constraint conditions, and this application uses the Drools rule engine to integrate thresholds and constraints.

[0085] Exemplarily, the calculation formula for the dynamic threshold of approval time limit is: , where is the target approval time limit for the kth working stage (unit: hour); is the average approval duration of the ith similar matter in historical data (baseline value); is the complexity score of the ith matter (level 1-5, generated by step S202); is the highest complexity level defined by the system (fixed value 5); is the dynamic adjustment coefficient for the ith matter (such as the acceleration ratio for urgent matters, generated by step S203); is the cross-departmental collaboration degree (0-1 value, calculation method: actual number of collaborating departments / number of departments that should collaborate); 、 and are trainable weight coefficients (obtained through model iteration optimization in step S203, for example = 0.6, = 0.4, = 0.2).

[0086] The formula for cross-departmental collaboration priority ranking is:

[0087] , where is the priority score of the jth cross-departmental collaboration matter (the larger the value, the higher the priority); is the urgency score (level 1-5, selected by the user when submitting or automatically determined by the system, such as social security card loss reporting is level 5); is the required resource amount (such as man-hours, system concurrency); is the total available resource amount of the system currently; is the current delay time (remaining duration from the promised completion time); is the maximum allowable delay time (such as 7 days for ordinary matters and 2 hours for urgent matters); 、 and are weight coefficients.

[0088] S30: Based on the historical business data set of the intelligent government service platform, calculate and determine the associated business factors between each government affairs process, and obtain the business factor correlation coefficients of all government affairs processes.

[0089] In this embodiment, the associated business factor refers to the external factors affecting process efficiency (such as holidays, the number of approval personnel, and the material sharing rate); the business factor correlation coefficient refers to the correlation strength between the factor and the approval time limit (such as the Pearson correlation coefficient r ∈ [-1, 1]).

[0090] Specifically, identify potential influencing factors from the government affairs system (such as "material digitization rate" and "number of cross-departmental collaborations"); use the Pearson correlation coefficient to calculate the association strength between the factor and the approval time limit. For example, it is found that the "material sharing rate" is positively correlated with the approval time limit (Pearson correlation coefficient r = 0.75), that is, the higher the sharing rate, the shorter the time-consuming; generate an n×n matrix (n is the number of government affairs processes) to obtain the correlation coefficient matrix for quantifying the indirect influence relationship between processes.

[0091] S40: In the intelligent decision-making model, according to the business factor correlation coefficients of all government affairs processes and the approval parameter adjustment strategy corresponding to the historical approval data set, determine the approval time limit target values for each government affairs process in each work stage interval, and generate the optimal data processing strategy.

[0092] In this embodiment, the approval parameter adjustment strategy refers to the rule for dynamically adjusting the approval resource allocation (such as increasing the manpower input to shorten the critical path); the time limit target value refers to the target completion time for each stage interval (such as "expert review stage ≤ 2 working days").

[0093] Specifically, input the correlation coefficient matrix and historical approval data into the intelligent decision-making model, and solve for the optimal time limit for each stage under the minimum total time-consuming based on the linear programming model. For example, through the constraint condition (total time-consuming ≤ 5 days), calculate that "material preliminary review ≤ 1 day" and "result issuance ≤ 2 days", and generate the optimal strategy file in JSON format, that is, obtain the optimal data processing strategy.

[0094] S50: Dynamically optimize and control the approval time limit of each government affairs process of the intelligent government service platform according to the optimal data processing strategy.

[0095] In this embodiment, the dynamic optimization and control refers to automatically adjusting the approval resource allocation based on real-time data; the feedback mechanism of the data processing strategy triggers the strategy update through monitoring indicators (such as current time-consuming and backlog volume).

[0096] It should be understood that the sequence numbers of the steps in the above embodiments do not indicate the order of execution, and the execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0097] In one embodiment, in particular, according to the embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present invention includes a computer program product including a computer program / instructions, and when the computer program / instructions are executed by a processor, the steps of a data processing method applied to an intelligent government service platform as described above are implemented. In such an embodiment, the computer program can be downloaded and installed from a network through a communication module and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), various functions defined in the present invention are executed.

[0098] Those skilled in the art can clearly understand that for the convenience and conciseness of description, only the above division of each functional unit and module is used as an example. In practical applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

[0099] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An intelligent government affairs service platform, characterized in that, Including: A public configuration module for hierarchically configuring the system service capabilities according to the received configuration instructions. The hierarchical configuration includes capability application management configuration, public template configuration, and service model configuration. The service model configuration includes a service overall planning model and a service implementation model; A reservation rule engine module, including multi-level reservation rules for lobby reservation rules, zone reservation rules, and matter reservation rules. The rule parameters of the multi-level reservation rules are dynamically adjusted based on the reservation status. The multi-level reservation rules include reservation time periods, government service number release strategies, and conflict detection mechanisms; A business processing module integrated with an electronic certificate library and a digital signature verification unit to achieve automated material verification and document generation in the scenario of handling business without certificates; The platform conducts government service data interaction with external systems through the capability application management module and authorizes the system service capabilities based on the received user login request.

2. An intelligent government affairs service platform according to claim 1, characterized in that The hierarchical configuration includes: When configuring the overall planning model, configuring government service content, process links, and intelligent service declaration rules based on a preset standardized matter model; When configuring the implementation model, obtaining service links corresponding to the government service content or the process links based on the overall planning model, binding link authorized personnel accounts, document templates, and handling channels based on the service links, and configuring review nodes; The public configuration module is connected to a visual configuration terminal. The visual configuration terminal receives configuration instructions for configuring the overall planning model and the implementation model, and synchronizes the configuration results to the business processing module for efficiency detection.

3. An intelligent government affairs service platform according to claim 1, characterized in that, The reservation rule engine module performs the following operations: When detecting conflicts in the multi-level reservation rules, dynamically adjusting the number source allocation based on the number release template management unit according to a preset priority strategy; Implementing encrypted storage and timed release of number sources in batches through the number release template management unit; The rule parameters of the multi-level reservation rules include the waiting list rule weight coefficients and blacklist update frequencies of each reservation rule.

4. An intelligent government affairs service platform according to claim 2, characterized in that, Configuring government service content, process links, and intelligent service declaration rules based on a preset standardized matter model, including: Associating the electronic form of government service content based on a preset standardized matter model, including: when selecting an electronic form, making an associated selection based on the retrieval fields of form name, administrative region, or competent department; after selecting the target form, the system loads the form fields and performs field-level mapping with the acceptance conditions and handling materials in the government service content; When associating handling materials, querying the electronic certificate library on the selection interface, and querying and filtering target electronic certificates by certificate name, administrative region, or competent department; When associating handling results, generating an electronic certificate template for the result materials based on the result generation instruction, and configuring the issuance rules including the issuing department and service validity period.

5. An intelligent government affairs service platform according to claim 2, characterized in that, In the overall planning model, the handling channels include offline halls, online APPs, or self-service terminals; the handling methods of the handling channels include unified channels and differentiated channels: In the overall planning model, all service handling items of the unified handling channel share the channel configuration; the differentiated channel configures the corresponding handling channel for each service handling item, and the handling channel is associated with the priority of the channel matters, and matters are handled based on the priority of the channel matters.

6. A data processing method applied to an intelligent government affairs service platform, characterized in that, Including: Obtain a configuration instruction, and perform hierarchical configuration on the system service capabilities according to the configuration instruction. The hierarchical configuration includes capability application management configuration, public template configuration, and service model configuration, where the service model configuration includes a service overall planning model and a service implementation model; Based on the appointment rule engine module, execute multi-level appointment rules. The multi-level appointment rules include hall appointment rules, special zone appointment rules, and matter appointment rules. Among them, the parameters of the multi-level appointment rules are dynamically adjusted based on the appointment status. The multi-level appointment rules include appointment time periods, government service number release strategies, and conflict detection mechanisms; Integrate the electronic certificate library and the digital signature verification unit through the business handling module to achieve automated material verification and document generation in the scenario of handling business without certificates; Perform government service data interaction with external systems through the capability application management module, and authorize the system service capabilities based on the received user login request.

7. A data processing method applied to an intelligent government affairs service platform according to claim 6, characterized in that, The service overall planning model is used to overall plan the resource allocation and process coordination between different government affairs matters, and the service implementation model is used to define the service path, approval nodes, and service interfaces of specific matters; The dynamic adjustment of the appointment rules includes: optimizing the division of appointment time periods and the number release frequency according to the real-time appointment number, resource usage situation, and historical appointment data; The conflict detection mechanism is used to identify time conflicts, personnel conflicts, and resource conflicts during the appointment process, and trigger an early warning or automatically reallocate when a conflict is detected.

8. A data processing method applied to an intelligent government service platform according to claim 6, characterized in that, The method further includes: Obtain the historical business operation data and business logic association rules during the operation of multiple government affairs processes based on the historical business data set of the intelligent government service platform; the business logic association rules include multiple working stage intervals corresponding to different approval complexities; the government affairs process is associated with a unique business identification code; Obtain the historical approval data set of each government affairs process based on the business identification code, and perform training and optimization based on the approval complexity in the preset initial data processing model to obtain an intelligent decision-making model; Calculate and determine the associated business factors between each government affairs process based on the historical business data set of the intelligent government service platform to obtain the business factor correlation coefficients of all government affairs processes; In the intelligent decision-making model, according to the business factor correlation coefficients of all government affairs processes and the approval parameter adjustment strategy corresponding to the historical approval data set, determine the approval time limit target values of each government affairs process in each working stage interval, and generate an optimal data processing strategy; Dynamically optimize and control the approval time limit of each government affairs process of the intelligent government service platform according to the optimal data processing strategy.

9. A data processing method applied to an intelligent government affairs service platform according to claim 8, characterized in that, The obtaining of the historical business operation data and business logic association rules during the operation of multiple government affairs processes based on the historical business data set of the intelligent government service platform includes: Obtain the business handling records and corresponding manual intervention frequency data of each government affairs process during the historical service cycle based on the historical business data set of the intelligent government affairs service platform; Create multiple historical service time intervals according to the business handling records and manual intervention frequency data; Based on multiple historical service time intervals, divide the business handling records and manual intervention frequency data of each government affairs process based on the business identification code, and correspondingly obtain multiple historical business operation data of each government affairs process; Determine the differentiated business logic association rules of each government affairs process according to the manual intervention frequency data and the preset logical rule judgment conditions in multiple historical business operation data.

10. A data processing method applied to an intelligent government affairs service platform according to claim 8, characterized in that, Obtain the historical approval data set of each government affairs process based on the business identification code, and perform training and optimization based on the approval complexity in the preset initial data processing model to obtain an intelligent decision-making model, including: Extract the approval stage feature data of each government affairs process according to the business identification code, including the duration of each approval link, the material transfer path, and the time-consuming of cross-departmental collaboration; Construct a multi-dimensional approval complexity evaluation index according to the overtime nodes and repeated submission nodes in the approval stage feature data; Input the historical approval data set with marked approval complexity levels into the initial data processing model, and use the dynamic weight adjustment algorithm to perform iterative training on the initial data processing model, so that the data processing model learns the approval time optimization rules in different complexity scenarios; Based on the trained data processing model, output the time threshold parameters of each approval link, and combine the cross-departmental collaboration efficiency constraint conditions to generate an intelligent decision-making model adapted to the current government affairs process.

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